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Data Analysis Presentation Templates

All business people, entrepreneurs, and sales executives listen up every high-quality presentation should be based on reliable research and analysis tools. use these amazing free data analysis powerpoint templates and google slides themes to make sure your ppt hits the nail on the head..

Easy-to-Use Free Data Analysis PowerPoint Templates and Google Slides Themes for Simplifying Your Data!

• Data Science: For showing how data can answer big questions.
• Data Analytics: To explain how you’ve dug into the data.
• Data Cleansing: To show how you’ve made the data clean and accurate.
• Backup and Recovery: To teach people how to keep their data safe.
• Support Model Diagrams: For when you want to show how things work together.
• Applications of Data Science: To share how data science can be used in real life.
• Data Analysis Tools: To introduce the tools that help with data work.
• Easy to Change: You can pick different colors, shapes, and backgrounds.
• Ready for Any Screen: They work in both standard (4:3) and widescreen (16:9) formats.
• For Everyone: Whether you’re a student, a teacher, or a business person, these slides are for you.

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What is a data analysis.

Data Analysis helps you inspect, clean, transform, and model data to discover useful information, informing conclusions, and support decision-making.

What are Data Analysis PowerPoint Templates?

You can use Data Analysis PowerPoint Templates to present data analysis information. These templates provide a framework for visualizing data analysis results and help presenters quickly create a visually appealing slide.

Where can we use these Data Analysis Slides?

You can use Data Analysis Slides in various ways, including presentations, marketing materials, reports, and as part of data science projects. You can also use them to visualize and explain data in classrooms and workshops.

How can I make Data Analysis PPT Slides in a presentation?

Choose an appropriate template for your presentation. There are many online templates available for free in Slide Egg. Ensure that the data you select is relevant to the topic and is presented in an easy-to-understand way. Suppose you want to learn how to use the PowerPoint tool. Visit Tips and tricks for detailed instructions.

Who can use Data Analysis PPT Templates?

Anyone can use Data Analysis PPT Templates to present data in a professional and organized manner. They are handy for businesses, researchers, and students.

Why do we need Data Analysis PowerPoint Slides?

Data Analysis PowerPoint slides provide the ability to quickly and effectively communicate the results of data analysis to an audience. These slides also include visuals, such as charts and graphs, to support the research.

Where can I find free Data Analysis PPT Templates?

Many websites offer free Data Analysis PPT templates. Slide egg is one of the best PowerPoint providers. Our websites' uniquely designed templates help you to identify trends, outliers, and correlations to identify potential areas for improvement.

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Data Analysis Presentation Template

  Data analysis is the key to exploring your global attributes as a business. When you are looking to fundraise by inviting venture capitalists to your company, you should have a Data Analysis Presentation Template to highlight your business reach and standings.

So, this creative template should be a must added slide to your business presentation collection to show the geography and history of your business. As a single slide, it has many uses.

For example, you can condense your presentation within the limit of the one-pager template by showing the key metrics in the platform.

On the other hand, you can add this template as a cover slide of your PowerPoint collection featuring an investment presentation.    

Data Analysis Presentation Templates carry a thematic theme filled with a data line image. The users can present facts and figures by incorporating charts, graphs, and other statistical diagrams.

Data analysis is all about digging deep into data, sorting it out, cleaning it up, and then turning it into valuable insights. It’s like selecting through a pile of information to find the hidden gems that can help us make better decisions.

We use different tools and methods, like statistics and machine learning, to make sense of the data and spot trends or patterns. It’s pretty crucial across various fields, like business and science, where understanding data helps us steer our way towards success.  

Data Analysis PowerPoint Template is 100% editable by altering its features. The users can change color, font, size, and images whenever they need to recreate. Alterations never mess up the resolutions and the content view.

It helps to showcase financial reports, marketing analytics, research findings, performance metrics and much more.

So, business analysts, data scientists, teachers, researchers marketing professionals and anyone who have  engaged in data collection, processing, analysis, and verification can download data analysis presentation templates to provide crystal clear data to their audiences. Grab it now!  

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Present Your Data Like a Pro

• Joel Schwartzberg

Demystify the numbers. Your audience will thank you.

While a good presentation has data, data alone doesn’t guarantee a good presentation. It’s all about how that data is presented. The quickest way to confuse your audience is by sharing too many details at once. The only data points you should share are those that significantly support your point — and ideally, one point per chart. To avoid the debacle of sheepishly translating hard-to-see numbers and labels, rehearse your presentation with colleagues sitting as far away as the actual audience would. While you’ve been working with the same chart for weeks or months, your audience will be exposed to it for mere seconds. Give them the best chance of comprehending your data by using simple, clear, and complete language to identify X and Y axes, pie pieces, bars, and other diagrammatic elements. Try to avoid abbreviations that aren’t obvious, and don’t assume labeled components on one slide will be remembered on subsequent slides. Every valuable chart or pie graph has an “Aha!” zone — a number or range of data that reveals something crucial to your point. Make sure you visually highlight the “Aha!” zone, reinforcing the moment by explaining it to your audience.

With so many ways to spin and distort information these days, a presentation needs to do more than simply share great ideas — it needs to support those ideas with credible data. That’s true whether you’re an executive pitching new business clients, a vendor selling her services, or a CEO making a case for change.

• JS Joel Schwartzberg oversees executive communications for a major national nonprofit, is a professional presentation coach, and is the author of Get to the Point! Sharpen Your Message and Make Your Words Matter and The Language of Leadership: How to Engage and Inspire Your Team . You can find him on LinkedIn and X. TheJoelTruth

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Home Blog Design Understanding Data Presentations (Guide + Examples)

Understanding Data Presentations (Guide + Examples)

In this age of overwhelming information, the skill to effectively convey data has become extremely valuable. Initiating a discussion on data presentation types involves thoughtful consideration of the nature of your data and the message you aim to convey. Different types of visualizations serve distinct purposes. Whether you’re dealing with how to develop a report or simply trying to communicate complex information, how you present data influences how well your audience understands and engages with it. This extensive guide leads you through the different ways of data presentation.

Table of Contents

What is a Data Presentation?

What should a data presentation include, line graphs, treemap chart, scatter plot, how to choose a data presentation type, recommended data presentation templates, common mistakes done in data presentation.

A data presentation is a slide deck that aims to disclose quantitative information to an audience through the use of visual formats and narrative techniques derived from data analysis, making complex data understandable and actionable. This process requires a series of tools, such as charts, graphs, tables, infographics, dashboards, and so on, supported by concise textual explanations to improve understanding and boost retention rate.

Data presentations require us to cull data in a format that allows the presenter to highlight trends, patterns, and insights so that the audience can act upon the shared information. In a few words, the goal of data presentations is to enable viewers to grasp complicated concepts or trends quickly, facilitating informed decision-making or deeper analysis.

Data presentations go beyond the mere usage of graphical elements. Seasoned presenters encompass visuals with the art of data storytelling , so the speech skillfully connects the points through a narrative that resonates with the audience. Depending on the purpose – inspire, persuade, inform, support decision-making processes, etc. – is the data presentation format that is better suited to help us in this journey.

To nail your upcoming data presentation, ensure to count with the following elements:

• Clear Objectives: Understand the intent of your presentation before selecting the graphical layout and metaphors to make content easier to grasp.
• Engaging introduction: Use a powerful hook from the get-go. For instance, you can ask a big question or present a problem that your data will answer. Take a look at our guide on how to start a presentation for tips & insights.
• Structured Narrative: Your data presentation must tell a coherent story. This means a beginning where you present the context, a middle section in which you present the data, and an ending that uses a call-to-action. Check our guide on presentation structure for further information.
• Visual Elements: These are the charts, graphs, and other elements of visual communication we ought to use to present data. This article will cover one by one the different types of data representation methods we can use, and provide further guidance on choosing between them.
• Insights and Analysis: This is not just showcasing a graph and letting people get an idea about it. A proper data presentation includes the interpretation of that data, the reason why it’s included, and why it matters to your research.
• Conclusion & CTA: Ending your presentation with a call to action is necessary. Whether you intend to wow your audience into acquiring your services, inspire them to change the world, or whatever the purpose of your presentation, there must be a stage in which you convey all that you shared and show the path to staying in touch. Plan ahead whether you want to use a thank-you slide, a video presentation, or which method is apt and tailored to the kind of presentation you deliver.
• Q&A Session: After your speech is concluded, allocate 3-5 minutes for the audience to raise any questions about the information you disclosed. This is an extra chance to establish your authority on the topic. Check our guide on questions and answer sessions in presentations here.

Bar charts are a graphical representation of data using rectangular bars to show quantities or frequencies in an established category. They make it easy for readers to spot patterns or trends. Bar charts can be horizontal or vertical, although the vertical format is commonly known as a column chart. They display categorical, discrete, or continuous variables grouped in class intervals [1] . They include an axis and a set of labeled bars horizontally or vertically. These bars represent the frequencies of variable values or the values themselves. Numbers on the y-axis of a vertical bar chart or the x-axis of a horizontal bar chart are called the scale.

Real-Life Application of Bar Charts

Let’s say a sales manager is presenting sales to their audience. Using a bar chart, he follows these steps.

Step 1: Selecting Data

The first step is to identify the specific data you will present to your audience.

The sales manager has highlighted these products for the presentation.

• Product A: Men’s Shoes
• Product B: Women’s Apparel
• Product C: Electronics
• Product D: Home Decor

Step 2: Choosing Orientation

Opt for a vertical layout for simplicity. Vertical bar charts help compare different categories in case there are not too many categories [1] . They can also help show different trends. A vertical bar chart is used where each bar represents one of the four chosen products. After plotting the data, it is seen that the height of each bar directly represents the sales performance of the respective product.

It is visible that the tallest bar (Electronics – Product C) is showing the highest sales. However, the shorter bars (Women’s Apparel – Product B and Home Decor – Product D) need attention. It indicates areas that require further analysis or strategies for improvement.

Step 3: Colorful Insights

Different colors are used to differentiate each product. It is essential to show a color-coded chart where the audience can distinguish between products.

• Men’s Shoes (Product A): Yellow
• Women’s Apparel (Product B): Orange
• Electronics (Product C): Violet
• Home Decor (Product D): Blue

Bar charts are straightforward and easily understandable for presenting data. They are versatile when comparing products or any categorical data [2] . Bar charts adapt seamlessly to retail scenarios. Despite that, bar charts have a few shortcomings. They cannot illustrate data trends over time. Besides, overloading the chart with numerous products can lead to visual clutter, diminishing its effectiveness.

For more information, check our collection of bar chart templates for PowerPoint .

Line graphs help illustrate data trends, progressions, or fluctuations by connecting a series of data points called ‘markers’ with straight line segments. This provides a straightforward representation of how values change [5] . Their versatility makes them invaluable for scenarios requiring a visual understanding of continuous data. In addition, line graphs are also useful for comparing multiple datasets over the same timeline. Using multiple line graphs allows us to compare more than one data set. They simplify complex information so the audience can quickly grasp the ups and downs of values. From tracking stock prices to analyzing experimental results, you can use line graphs to show how data changes over a continuous timeline. They show trends with simplicity and clarity.

Real-life Application of Line Graphs

To understand line graphs thoroughly, we will use a real case. Imagine you’re a financial analyst presenting a tech company’s monthly sales for a licensed product over the past year. Investors want insights into sales behavior by month, how market trends may have influenced sales performance and reception to the new pricing strategy. To present data via a line graph, you will complete these steps.

First, you need to gather the data. In this case, your data will be the sales numbers. For example:

• January: $45,000
• February: $55,000
• March: $45,000
• April: $60,000
• May: $ 70,000
• June: $65,000
• July: $62,000
• August: $68,000
• September: $81,000
• October: $76,000
• November: $87,000
• December: $91,000

After choosing the data, the next step is to select the orientation. Like bar charts, you can use vertical or horizontal line graphs. However, we want to keep this simple, so we will keep the timeline (x-axis) horizontal while the sales numbers (y-axis) vertical.

Step 3: Connecting Trends

After adding the data to your preferred software, you will plot a line graph. In the graph, each month’s sales are represented by data points connected by a line.

Step 4: Adding Clarity with Color

If there are multiple lines, you can also add colors to highlight each one, making it easier to follow.

Line graphs excel at visually presenting trends over time. These presentation aids identify patterns, like upward or downward trends. However, too many data points can clutter the graph, making it harder to interpret. Line graphs work best with continuous data but are not suitable for categories.

For more information, check our collection of line chart templates for PowerPoint and our article about how to make a presentation graph .

A data dashboard is a visual tool for analyzing information. Different graphs, charts, and tables are consolidated in a layout to showcase the information required to achieve one or more objectives. Dashboards help quickly see Key Performance Indicators (KPIs). You don’t make new visuals in the dashboard; instead, you use it to display visuals you’ve already made in worksheets [3] .

Keeping the number of visuals on a dashboard to three or four is recommended. Adding too many can make it hard to see the main points [4]. Dashboards can be used for business analytics to analyze sales, revenue, and marketing metrics at a time. They are also used in the manufacturing industry, as they allow users to grasp the entire production scenario at the moment while tracking the core KPIs for each line.

Real-Life Application of a Dashboard

Consider a project manager presenting a software development project’s progress to a tech company’s leadership team. He follows the following steps.

Step 1: Defining Key Metrics

To effectively communicate the project’s status, identify key metrics such as completion status, budget, and bug resolution rates. Then, choose measurable metrics aligned with project objectives.

Step 2: Choosing Visualization Widgets

After finalizing the data, presentation aids that align with each metric are selected. For this project, the project manager chooses a progress bar for the completion status and uses bar charts for budget allocation. Likewise, he implements line charts for bug resolution rates.

Step 3: Dashboard Layout

Key metrics are prominently placed in the dashboard for easy visibility, and the manager ensures that it appears clean and organized.

Dashboards provide a comprehensive view of key project metrics. Users can interact with data, customize views, and drill down for detailed analysis. However, creating an effective dashboard requires careful planning to avoid clutter. Besides, dashboards rely on the availability and accuracy of underlying data sources.

For more information, check our article on how to design a dashboard presentation , and discover our collection of dashboard PowerPoint templates .

Treemap charts represent hierarchical data structured in a series of nested rectangles [6] . As each branch of the ‘tree’ is given a rectangle, smaller tiles can be seen representing sub-branches, meaning elements on a lower hierarchical level than the parent rectangle. Each one of those rectangular nodes is built by representing an area proportional to the specified data dimension.

Treemaps are useful for visualizing large datasets in compact space. It is easy to identify patterns, such as which categories are dominant. Common applications of the treemap chart are seen in the IT industry, such as resource allocation, disk space management, website analytics, etc. Also, they can be used in multiple industries like healthcare data analysis, market share across different product categories, or even in finance to visualize portfolios.

Real-Life Application of a Treemap Chart

Let’s consider a financial scenario where a financial team wants to represent the budget allocation of a company. There is a hierarchy in the process, so it is helpful to use a treemap chart. In the chart, the top-level rectangle could represent the total budget, and it would be subdivided into smaller rectangles, each denoting a specific department. Further subdivisions within these smaller rectangles might represent individual projects or cost categories.

Step 1: Define Your Data Hierarchy

While presenting data on the budget allocation, start by outlining the hierarchical structure. The sequence will be like the overall budget at the top, followed by departments, projects within each department, and finally, individual cost categories for each project.

• Top-level rectangle: Total Budget
• Second-level rectangles: Departments (Engineering, Marketing, Sales)
• Third-level rectangles: Projects within each department
• Fourth-level rectangles: Cost categories for each project (Personnel, Marketing Expenses, Equipment)

Step 2: Choose a Suitable Tool

It’s time to select a data visualization tool supporting Treemaps. Popular choices include Tableau, Microsoft Power BI, PowerPoint, or even coding with libraries like D3.js. It is vital to ensure that the chosen tool provides customization options for colors, labels, and hierarchical structures.

Here, the team uses PowerPoint for this guide because of its user-friendly interface and robust Treemap capabilities.

Step 3: Make a Treemap Chart with PowerPoint

After opening the PowerPoint presentation, they chose “SmartArt” to form the chart. The SmartArt Graphic window has a “Hierarchy” category on the left.  Here, you will see multiple options. You can choose any layout that resembles a Treemap. The “Table Hierarchy” or “Organization Chart” options can be adapted. The team selects the Table Hierarchy as it looks close to a Treemap.

Step 5: Input Your Data

After that, a new window will open with a basic structure. They add the data one by one by clicking on the text boxes. They start with the top-level rectangle, representing the total budget.  

Step 6: Customize the Treemap

By clicking on each shape, they customize its color, size, and label. At the same time, they can adjust the font size, style, and color of labels by using the options in the “Format” tab in PowerPoint. Using different colors for each level enhances the visual difference.

Treemaps excel at illustrating hierarchical structures. These charts make it easy to understand relationships and dependencies. They efficiently use space, compactly displaying a large amount of data, reducing the need for excessive scrolling or navigation. Additionally, using colors enhances the understanding of data by representing different variables or categories.

In some cases, treemaps might become complex, especially with deep hierarchies.  It becomes challenging for some users to interpret the chart. At the same time, displaying detailed information within each rectangle might be constrained by space. It potentially limits the amount of data that can be shown clearly. Without proper labeling and color coding, there’s a risk of misinterpretation.

A heatmap is a data visualization tool that uses color coding to represent values across a two-dimensional surface. In these, colors replace numbers to indicate the magnitude of each cell. This color-shaded matrix display is valuable for summarizing and understanding data sets with a glance [7] . The intensity of the color corresponds to the value it represents, making it easy to identify patterns, trends, and variations in the data.

As a tool, heatmaps help businesses analyze website interactions, revealing user behavior patterns and preferences to enhance overall user experience. In addition, companies use heatmaps to assess content engagement, identifying popular sections and areas of improvement for more effective communication. They excel at highlighting patterns and trends in large datasets, making it easy to identify areas of interest.

We can implement heatmaps to express multiple data types, such as numerical values, percentages, or even categorical data. Heatmaps help us easily spot areas with lots of activity, making them helpful in figuring out clusters [8] . When making these maps, it is important to pick colors carefully. The colors need to show the differences between groups or levels of something. And it is good to use colors that people with colorblindness can easily see.

Check our detailed guide on how to create a heatmap here. Also discover our collection of heatmap PowerPoint templates .

Pie charts are circular statistical graphics divided into slices to illustrate numerical proportions. Each slice represents a proportionate part of the whole, making it easy to visualize the contribution of each component to the total.

The size of the pie charts is influenced by the value of data points within each pie. The total of all data points in a pie determines its size. The pie with the highest data points appears as the largest, whereas the others are proportionally smaller. However, you can present all pies of the same size if proportional representation is not required [9] . Sometimes, pie charts are difficult to read, or additional information is required. A variation of this tool can be used instead, known as the donut chart , which has the same structure but a blank center, creating a ring shape. Presenters can add extra information, and the ring shape helps to declutter the graph.

Pie charts are used in business to show percentage distribution, compare relative sizes of categories, or present straightforward data sets where visualizing ratios is essential.

Real-Life Application of Pie Charts

Consider a scenario where you want to represent the distribution of the data. Each slice of the pie chart would represent a different category, and the size of each slice would indicate the percentage of the total portion allocated to that category.

Step 1: Define Your Data Structure

Imagine you are presenting the distribution of a project budget among different expense categories.

• Column A: Expense Categories (Personnel, Equipment, Marketing, Miscellaneous)
• Column B: Budget Amounts ($40,000, $30,000, $20,000, $10,000) Column B represents the values of your categories in Column A.

Step 2: Insert a Pie Chart

Using any of the accessible tools, you can create a pie chart. The most convenient tools for forming a pie chart in a presentation are presentation tools such as PowerPoint or Google Slides.  You will notice that the pie chart assigns each expense category a percentage of the total budget by dividing it by the total budget.

For instance:

• Personnel: $40,000 / ($40,000 + $30,000 + $20,000 + $10,000) = 40%
• Equipment: $30,000 / ($40,000 + $30,000 + $20,000 + $10,000) = 30%
• Marketing: $20,000 / ($40,000 + $30,000 + $20,000 + $10,000) = 20%
• Miscellaneous: $10,000 / ($40,000 + $30,000 + $20,000 + $10,000) = 10%

You can make a chart out of this or just pull out the pie chart from the data.

3D pie charts and 3D donut charts are quite popular among the audience. They stand out as visual elements in any presentation slide, so let’s take a look at how our pie chart example would look in 3D pie chart format.

Step 03: Results Interpretation

The pie chart visually illustrates the distribution of the project budget among different expense categories. Personnel constitutes the largest portion at 40%, followed by equipment at 30%, marketing at 20%, and miscellaneous at 10%. This breakdown provides a clear overview of where the project funds are allocated, which helps in informed decision-making and resource management. It is evident that personnel are a significant investment, emphasizing their importance in the overall project budget.

Pie charts provide a straightforward way to represent proportions and percentages. They are easy to understand, even for individuals with limited data analysis experience. These charts work well for small datasets with a limited number of categories.

However, a pie chart can become cluttered and less effective in situations with many categories. Accurate interpretation may be challenging, especially when dealing with slight differences in slice sizes. In addition, these charts are static and do not effectively convey trends over time.

For more information, check our collection of pie chart templates for PowerPoint .

Histograms present the distribution of numerical variables. Unlike a bar chart that records each unique response separately, histograms organize numeric responses into bins and show the frequency of reactions within each bin [10] . The x-axis of a histogram shows the range of values for a numeric variable. At the same time, the y-axis indicates the relative frequencies (percentage of the total counts) for that range of values.

Whenever you want to understand the distribution of your data, check which values are more common, or identify outliers, histograms are your go-to. Think of them as a spotlight on the story your data is telling. A histogram can provide a quick and insightful overview if you’re curious about exam scores, sales figures, or any numerical data distribution.

Real-Life Application of a Histogram

In the histogram data analysis presentation example, imagine an instructor analyzing a class’s grades to identify the most common score range. A histogram could effectively display the distribution. It will show whether most students scored in the average range or if there are significant outliers.

Step 1: Gather Data

He begins by gathering the data. The scores of each student in class are gathered to analyze exam scores.

After arranging the scores in ascending order, bin ranges are set.

Step 2: Define Bins

Bins are like categories that group similar values. Think of them as buckets that organize your data. The presenter decides how wide each bin should be based on the range of the values. For instance, the instructor sets the bin ranges based on score intervals: 60-69, 70-79, 80-89, and 90-100.

Step 3: Count Frequency

Now, he counts how many data points fall into each bin. This step is crucial because it tells you how often specific ranges of values occur. The result is the frequency distribution, showing the occurrences of each group.

Here, the instructor counts the number of students in each category.

• 60-69: 1 student (Kate)
• 70-79: 4 students (David, Emma, Grace, Jack)
• 80-89: 7 students (Alice, Bob, Frank, Isabel, Liam, Mia, Noah)
• 90-100: 3 students (Clara, Henry, Olivia)

Step 4: Create the Histogram

It’s time to turn the data into a visual representation. Draw a bar for each bin on a graph. The width of the bar should correspond to the range of the bin, and the height should correspond to the frequency.  To make your histogram understandable, label the X and Y axes.

In this case, the X-axis should represent the bins (e.g., test score ranges), and the Y-axis represents the frequency.

The histogram of the class grades reveals insightful patterns in the distribution. Most students, with seven students, fall within the 80-89 score range. The histogram provides a clear visualization of the class’s performance. It showcases a concentration of grades in the upper-middle range with few outliers at both ends. This analysis helps in understanding the overall academic standing of the class. It also identifies the areas for potential improvement or recognition.

Thus, histograms provide a clear visual representation of data distribution. They are easy to interpret, even for those without a statistical background. They apply to various types of data, including continuous and discrete variables. One weak point is that histograms do not capture detailed patterns in students’ data, with seven compared to other visualization methods.

A scatter plot is a graphical representation of the relationship between two variables. It consists of individual data points on a two-dimensional plane. This plane plots one variable on the x-axis and the other on the y-axis. Each point represents a unique observation. It visualizes patterns, trends, or correlations between the two variables.

Scatter plots are also effective in revealing the strength and direction of relationships. They identify outliers and assess the overall distribution of data points. The points’ dispersion and clustering reflect the relationship’s nature, whether it is positive, negative, or lacks a discernible pattern. In business, scatter plots assess relationships between variables such as marketing cost and sales revenue. They help present data correlations and decision-making.

Real-Life Application of Scatter Plot

A group of scientists is conducting a study on the relationship between daily hours of screen time and sleep quality. After reviewing the data, they managed to create this table to help them build a scatter plot graph:

In the provided example, the x-axis represents Daily Hours of Screen Time, and the y-axis represents the Sleep Quality Rating.

The scientists observe a negative correlation between the amount of screen time and the quality of sleep. This is consistent with their hypothesis that blue light, especially before bedtime, has a significant impact on sleep quality and metabolic processes.

There are a few things to remember when using a scatter plot. Even when a scatter diagram indicates a relationship, it doesn’t mean one variable affects the other. A third factor can influence both variables. The more the plot resembles a straight line, the stronger the relationship is perceived [11] . If it suggests no ties, the observed pattern might be due to random fluctuations in data. When the scatter diagram depicts no correlation, whether the data might be stratified is worth considering.

Choosing the appropriate data presentation type is crucial when making a presentation . Understanding the nature of your data and the message you intend to convey will guide this selection process. For instance, when showcasing quantitative relationships, scatter plots become instrumental in revealing correlations between variables. If the focus is on emphasizing parts of a whole, pie charts offer a concise display of proportions. Histograms, on the other hand, prove valuable for illustrating distributions and frequency patterns. 

Bar charts provide a clear visual comparison of different categories. Likewise, line charts excel in showcasing trends over time, while tables are ideal for detailed data examination. Starting a presentation on data presentation types involves evaluating the specific information you want to communicate and selecting the format that aligns with your message. This ensures clarity and resonance with your audience from the beginning of your presentation.

1. Fact Sheet Dashboard for Data Presentation

Convey all the data you need to present in this one-pager format, an ideal solution tailored for users looking for presentation aids. Global maps, donut chats, column graphs, and text neatly arranged in a clean layout presented in light and dark themes.

Use This Template

2. 3D Column Chart Infographic PPT Template

Represent column charts in a highly visual 3D format with this PPT template. A creative way to present data, this template is entirely editable, and we can craft either a one-page infographic or a series of slides explaining what we intend to disclose point by point.

3. Data Circles Infographic PowerPoint Template

An alternative to the pie chart and donut chart diagrams, this template features a series of curved shapes with bubble callouts as ways of presenting data. Expand the information for each arch in the text placeholder areas.

4. Colorful Metrics Dashboard for Data Presentation

This versatile dashboard template helps us in the presentation of the data by offering several graphs and methods to convert numbers into graphics. Implement it for e-commerce projects, financial projections, project development, and more.

5. Animated Data Presentation Tools for PowerPoint & Google Slides

A slide deck filled with most of the tools mentioned in this article, from bar charts, column charts, treemap graphs, pie charts, histogram, etc. Animated effects make each slide look dynamic when sharing data with stakeholders.

6. Statistics Waffle Charts PPT Template for Data Presentations

This PPT template helps us how to present data beyond the typical pie chart representation. It is widely used for demographics, so it’s a great fit for marketing teams, data science professionals, HR personnel, and more.

7. Data Presentation Dashboard Template for Google Slides

A compendium of tools in dashboard format featuring line graphs, bar charts, column charts, and neatly arranged placeholder text areas. 

8. Weather Dashboard for Data Presentation

Share weather data for agricultural presentation topics, environmental studies, or any kind of presentation that requires a highly visual layout for weather forecasting on a single day. Two color themes are available.

9. Social Media Marketing Dashboard Data Presentation Template

Intended for marketing professionals, this dashboard template for data presentation is a tool for presenting data analytics from social media channels. Two slide layouts featuring line graphs and column charts.

10. Project Management Summary Dashboard Template

A tool crafted for project managers to deliver highly visual reports on a project’s completion, the profits it delivered for the company, and expenses/time required to execute it. 4 different color layouts are available.

11. Profit & Loss Dashboard for PowerPoint and Google Slides

A must-have for finance professionals. This typical profit & loss dashboard includes progress bars, donut charts, column charts, line graphs, and everything that’s required to deliver a comprehensive report about a company’s financial situation.

Overwhelming visuals

One of the mistakes related to using data-presenting methods is including too much data or using overly complex visualizations. They can confuse the audience and dilute the key message.

Inappropriate chart types

Choosing the wrong type of chart for the data at hand can lead to misinterpretation. For example, using a pie chart for data that doesn’t represent parts of a whole is not right.

Lack of context

Failing to provide context or sufficient labeling can make it challenging for the audience to understand the significance of the presented data.

Inconsistency in design

Using inconsistent design elements and color schemes across different visualizations can create confusion and visual disarray.

Failure to provide details

Simply presenting raw data without offering clear insights or takeaways can leave the audience without a meaningful conclusion.

Lack of focus

Not having a clear focus on the key message or main takeaway can result in a presentation that lacks a central theme.

Visual accessibility issues

Overlooking the visual accessibility of charts and graphs can exclude certain audience members who may have difficulty interpreting visual information.

In order to avoid these mistakes in data presentation, presenters can benefit from using presentation templates . These templates provide a structured framework. They ensure consistency, clarity, and an aesthetically pleasing design, enhancing data communication’s overall impact.

Understanding and choosing data presentation types are pivotal in effective communication. Each method serves a unique purpose, so selecting the appropriate one depends on the nature of the data and the message to be conveyed. The diverse array of presentation types offers versatility in visually representing information, from bar charts showing values to pie charts illustrating proportions. 

Using the proper method enhances clarity, engages the audience, and ensures that data sets are not just presented but comprehensively understood. By appreciating the strengths and limitations of different presentation types, communicators can tailor their approach to convey information accurately, developing a deeper connection between data and audience understanding.

[1] Government of Canada, S.C. (2021) 5 Data Visualization 5.2 Bar Chart , 5.2 Bar chart .  https://www150.statcan.gc.ca/n1/edu/power-pouvoir/ch9/bargraph-diagrammeabarres/5214818-eng.htm

[2] Kosslyn, S.M., 1989. Understanding charts and graphs. Applied cognitive psychology, 3(3), pp.185-225. https://apps.dtic.mil/sti/pdfs/ADA183409.pdf

[3] Creating a Dashboard . https://it.tufts.edu/book/export/html/1870

[4] https://www.goldenwestcollege.edu/research/data-and-more/data-dashboards/index.html

[5] https://www.mit.edu/course/21/21.guide/grf-line.htm

[6] Jadeja, M. and Shah, K., 2015, January. Tree-Map: A Visualization Tool for Large Data. In GSB@ SIGIR (pp. 9-13). https://ceur-ws.org/Vol-1393/gsb15proceedings.pdf#page=15

[7] Heat Maps and Quilt Plots. https://www.publichealth.columbia.edu/research/population-health-methods/heat-maps-and-quilt-plots

[8] EIU QGIS WORKSHOP. https://www.eiu.edu/qgisworkshop/heatmaps.php

[9] About Pie Charts.  https://www.mit.edu/~mbarker/formula1/f1help/11-ch-c8.htm

[10] Histograms. https://sites.utexas.edu/sos/guided/descriptive/numericaldd/descriptiven2/histogram/ [11] https://asq.org/quality-resources/scatter-diagram

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7 PPT Templates for Comprehensive IT and Data Analytics Presentations

Last Updated on February 26, 2024 by Rosemary

If you’re working in the IT, data science, or data analytics field or have a presentation to prepare, get inspired by our visual examples of how you can enhance the slides. 

Explaining abstract IT concepts such as information sources, processes, or data structures requires ensuring that your audience will quickly understand what you want to present. The best way to address it is to use a visual form that is easy to grasp.

Explore our Business Performance PPT Reports category on the website for more resources to boost your presentation impact.

Therefore try to express complex IT ideas with diagrams and simple infographics. You can illustrate specific concepts with graphical symbols or show data flows using distinctive colors. The key thing is to keep visual clarity, to avoid a reader being lost. 

Importance of visual communication when presenting data processes and structures

PowerPoint can be the right tool for presenting complex IT frameworks thanks to its flexibility if used right. Check out the following PPT templates with data-related graphics we’ve put together to help visualize various IT concepts. All these templates contain editable visuals to help you successfully communicate your ideas to the target group; whether this is your project team, pitching a software company, or teaching university students.

Keep reading to get inspired by the data analytics and IT templates for making illustrative presentations effortlessly.

All the slides presented in this post, and many more, can be found by clicking on the pictures. Check out the whole data analytics and IT diagrams PPT collection here .

Depending on your presentation topic, you could use these seven PowerPoint templates:

• Digital transformation strategy roadmaps
• Web analytics report charts
• OLAP data cube 
• Artificial intelligence & machine learning
• DevOps know-how toolbox
• Blockchain technology 
• Data science icons

Digital Transformation Strategy Roadmaps Template

If you need to explain the digital transformation process and its effects on businesses, consider using roadmap visuals to explain the complexity of the process. The digital transformation strategy PPT template contains slides with digitalization definitions and quotes, development, opportunity and challenges, and diagrams and icons with use instructions.

The digital transformation visuals can be applied in the following cases:

• for educational purposes by trainers, lecturers, or teachers
• in IT project management by leaders or consultants e.g. introducing a new digitalization strategy inside a company or for a client.
• while introducing new tools and directions in a company strategy

Check also how roadmaps can be useful for other strategic presentations.

Web Analytics Reports Chart PowerPoint Template

Do you need to present an analysis of the page traffic source and user behavior? The general website health is important for launching advertising campaigns, minimizing the user bounce rate as much as possible, and reducing shopping cart abandonment. Proper communication of those concepts and their statistics to your team is an important step if you want to manage your online presence effectively. The following PowerPoint template was designed to support such presentations.  

The web analytics reports charts presentation deck contains pre-designed slides to illustrate Google Analytics findings, pie charts with share traffic sources distribution strategy visualization for improving digital marketing campaign failures, and a calendar for e-marketing project planning. Using such visuals can help you deliver the message to the desired audience in a transparent and understanding way.

This PPT template can be handy to improve understanding and collaboration between the marketing team web data analysts and eventually also developers. Marketers can follow the success of their campaigns, and developers can react promptly to keep the workflow smooth.

OLAP Data Cube PPT Graphics

Are you working in Big Data or explaining Business Intelligence concepts? Do you need to explain its essence, the OLAP cube? In that case, the Online Analytical Processing (OLAP) Template could be most suitable. It contains slides with OLAP definitions, data cube dimensions, cube elements explanation  (, visualization of slicing, drill-down, roll-up, and pivot data operations on OLAP, and a handful of icons and graphics for IT analytics.

These PPT graphics can help you to explain the OLAP concept to your colleagues, in reports or educational materials teaching data science essentials.

AI & Machine Learning Presentation

 If you are presenting topics related to Artificial Intelligence technologies, it’s a good idea to explain those concepts with graphics rather a text-heavy slides. The AI & machine learning PowerPoint template can be a useful help for your presentation preparation.  

You will find slides with definitions and quotes, AI, machine learning, deep learning comparisons, AI & ML history timeline, opportunities and dangers, and machine learning algorithm types. All slides contain illustrative diagrams and associative icons for presenting this dense information in an easier-to-grasp way.

We recommend you read the following article for more inspiration: How to Present Digital Technology Idea .

DevOps Know-How Diagrams

Do you work and talk about software development methodologies and processes? Then you can find useful the following DevOps diagrams collection to present it clearly. 

Check the PowerPoint graphics we designed to help you visually explain these topics. The DevOps know-how template contains a general DevOps introduction, a circle diagram with touchpoints for presenting the roles, and a honeycomb diagram explaining the advantages without stuffing the slide with text. You can also find flowchart diagrams with the 5 levels of DevOps and 4 phases.

You can further enrich your slides for better visualization with this IT icons bundle set .

Blockchain Technology Diagrams

Are you presenting the Blockchain technology or proposing a new project connected with it? Explaining such a complex technology can be difficult to grasp and often confusing. That is where graphic visuals may come as resourceful. The blockchain technology template contains slides with Blockchain definition, an introduction of how it works illustrated with a roadmap, its structure, key forces, applications, pros and cons, and editing instructions. 

Blockchain is increasingly being used in various industries such as real estate, travel and mobility, shipping and logistics, and product development. Therefore it’s worth having graphics by hand for explaining those concepts to your peers, and clients or for teaching purposes. For more blockchain topic inspirations, refer to this article .

Data Science Analytics PPT Icons

Need an idea on preparing big data, data analysis, or predictive analytics presentations? Using associative visuals will impress your audience and help them stay on the same page. The data science analytics graphics template is a collection of flat outline icons, flowcharts, and circle diagrams for simple concept comparisons such as data science, data analysis, and data mining. Slides with a dark background are also included inside, for more catchy presentations with emphasized elements.

Explore the PowerPoint slide deck mentioned above, it can be a good source for illustrations for data-related presentations, whether you are teaching about it or communicating IT concepts in meetings with your colleagues. See also how to make Big Data presentation appealing visually in PowerPoint.

IT & Data Analytics Presentations: Choosing the Right Template

We hope these PowerPoint Templates will help you find ideas for your next presentation about digital technologies and IT concepts. Introducing information-dense topics doesn’t need to be difficult if you are using the right visuals. Our inspiration for creating Data Analytics and IT templates was to help you communicate better, whether you do presentations to teach, inform or sell your IT services or solutions. You can adjust and reuse the slides and their graphic elements for different purposes depending on your goals.

Explore our YouTube channel for more creative inspiration:

Resources: PowerPoint Templates for IT and Data Analytics Presentations

You can find all the slides we used in this article in the infoDiagram graphics library. You can find many more illustrations to prepare professional presentations to impress your audience. See the whole deck collection here:

IT and Data Analytics Presentation PPT Templates

Want to test our graphics first? Check out this free PPT graphics sample kit and create unique slides by yourself from scratch.

• Data Science
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• AI ML DS Interview Series
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• Top 8 Free Dataset Sources to Use for Data Science Projects
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Final Year Projects for Data Science Portfolio

Building a robust portfolio is important for final-year data science students aiming to showcase their skills to potential employers. This article brings you 5 Portfolio Projects for Final Year Data Science Students that will help you showcase your skills in Artificial Intelligence (AI), Machine Learning (ML), and Data Science (DS).

Portfolio Projects for Final Year Data Science Students

Building a strong information technological know-how portfolio is an investment for your future career.

Table of Content

1. Wikipedia Text Scraping and cleaning

2. zomato data analysis using python, 3. wine quality prediction, 4. time series analysis with stock price data, 5. prediction of wine type using deep learning, choosing the right project for you, presentation and documentation tips.

Project Overview: Wikipedia data holds a wealth of information, but extracting it requires a two-step process: scraping and cleaning. Scraping involves techniques like using Python libraries to automatically harvest data from Wikipedia pages. However, it’s important to be respectful by checking the website’s guidelines and avoiding overwhelming their servers. Once you have the raw data, cleaning comes in. This involves removing HTML tags, filtering out infoboxes and references, and correcting inconsistencies in formatting or data types. By following ethical scraping practices and utilizing available tools, you can transform Wikipedia’s data into a usable format for further analysis.

• Scrape data from Wikipedia pages using Python libraries (e.g., BeautifulSoup, Scrapy).
• Clean the scraped data by removing HTML tags, infoboxes, references, and correcting inconsistencies.
• Store the cleaned data in a structured format for further analysis.

Skills Demonstrated

• Web scraping and data collection.
• Data cleaning and preprocessing.
• Use of Python libraries for data extraction and manipulation.
• Ethical web scraping practices.

You can refer to this article – Wikipedia Text Scraping and cleaning

Project Overview: Unveiling valuable insights from Zomato, a popular restaurant platform, requires the power of Python. Libraries like Pandas and Matplotlib become your allies in this task. Pandas helps you wrangle the Zomato data into a structured format, while Matplotlib brings it to life with informative visualizations. Through data exploration and analysis, you can uncover hidden trends. Perhaps you’ll identify popular cuisines by location or explore how pricing influences ratings. Python empowers you to ask questions of the data and uncover knowledge that can benefit both restaurants and diners.

• Collect and preprocess Zomato data.
• Perform exploratory data analysis (EDA) to identify trends and patterns.
• Visualize data using Matplotlib or Seaborn to uncover insights.
• Data wrangling and preprocessing using Pandas.
• Exploratory data analysis (EDA).
• Data visualization with Matplotlib or Seaborn.
• Insight generation and interpretation.

You can refer to this article – Zomato Data Analysis Using Python

Project Overview: Delving into the world of wine, machine learning offers a fascinating tool for predicting quality. By leveraging datasets containing wine attributes like acidity, alcohol content, and grape type, we can train models to identify patterns that influence a wine’s quality. This project explores these possibilities. Machine learning algorithms, like Support Vector Machines or Random Forests, analyze the data, learning to distinguish between high-quality and lower-quality wines. The ultimate goal? To create a model that can assess a new, unseen wine and accurately predict its quality based on its chemical makeup. This paves the way for winemakers to optimize production and for consumers to make informed choices.

• Preprocess and explore wine quality datasets.
• Train machine learning models (e.g., Support Vector Machines, Random Forests) to predict wine quality.
• Evaluate model performance using appropriate metrics.
• Data preprocessing and feature engineering.
• Machine learning model training and evaluation.
• Use of algorithms like Support Vector Machines and Random Forests.
• Interpretation of model results and actionable insights.

You can refer to this article – Wine Quality Prediction

Project Overview: Harnessing the power of time series analysis, this project unlocks insights from historical stock price data. By analyzing trends and patterns over time, we can attempt to predict future stock movements. The project will focus on techniques like ARIMA models or LSTMs to uncover hidden patterns within the data. These models can account for seasonality, trends, and cyclical behavior in stock prices. The ultimate objective is to broaden a model which could forecast destiny prices, even though it’s crucial to don’t forget predictions aren’t ensures. This project can serve as a treasured tool for investors seeking to make knowledgeable selections but ought to not be totally relied upon for financial recommendation.

• Collect and preprocess historical stock price data.
• Apply time series models (e.g., ARIMA, LSTM) to forecast future stock prices.
• Evaluate model performance and interpret results.
• Data preprocessing and handling time series data.
• Time series modeling and forecasting.
• Implementation of ARIMA and LSTM models.
• Model evaluation and prediction interpretation.

You can refer to this article – Time Series Analysis with Stock Price Data

This project explores the exciting possibilities of deep learning for classifying wine. Unlike traditional machine learning, deep learning uses multilayer artificial neural networks that mimic the structure of the brain. By feeding a deep learning model a data set rich in wine characteristics, such as chemical composition, aroma, and flavor profiles, the model can understand the complex relationships between these characteristics and specific wine types. You can learn. Imagine inputting model data from a new, unknown wine and being able to predict whether it’s Cabernet Sauvignon, Pinot Noir, or something else entirely. This project explores the power of deep learning to revolutionize wine classification and potentially assist sommeliers, producers, and connoisseurs in wine exploration.

• Preprocess and explore wine characteristic datasets.
• Develop a deep learning model using neural networks to classify wine types.
• Evaluate model performance and optimize for accuracy.
• Data preprocessing and exploration.
• Deep learning model development using frameworks like TensorFlow or Keras.
• Implementation of neural networks for classification.
• Model evaluation and optimization.

You can refer to this article – Prediction of Wine type using Deep Learning

• Pick something you love! Choose a project that grabs your interest. This will keep you motivated and make learning more enjoyable.
• Start small and grow big . Start with a project that matches your current skills. As you gain confidence, you can move on to more complex tasks.
• Show off a variety of skills. Aim for projects that use different techniques (like sorting things into categories, making predictions, and understanding written text).
• Focus on clean data. Remember: If you start with messy information, you’ll end up with messy results. Prioritise finding reliable datasets to work with.

Presentations:

• Clear and concise communication: Explain your task in a way that each technical and non-technical users can understand. Focus at the trouble you are solving, the method you used, and the important insights you received. Avoid jargon and complicated technical terms every time possible.
• Storytelling with data: More than just presenting records and figures. Use statistics visualisations (charts, graphs) to inform a compelling story about your result. Highlight any interesting trends or patterns that your project has uncovered.
• Interactive Visualisations (Optional): Consider using interactive dashboards or web applications to showcase your results and allow viewers to explore your findings more deeply. Tools like Streamlit, Plotly, or Dash can be helpful here.
• Presentation Tools: Utilise slides or interactive shows to successfully communicate your work during interviews or portfolio presentations. Tools like Jupyter Notebook or Google Colab may be exquisite for combining code, explanations, and visualisations.

Documentation:

• Project Overview: Provide a clear and concise precis of your mission goals, the technique you took, and the key effects you executed.
• Data and Methodology: Describe the facts you used, which includes its source and any preprocessing steps you completed. Explain the machine mastering algorithms or strategies you hired and why you chose them.
• Code Snippets: Include nicely-commented code snippets to demonstrate your implementation process. This lets in viewers to apprehend the common sense behind your code and potentially replicate your paintings.
• Results and Evaluation: Clearly explain the outcomes of your task and how you evaluated the overall performance of your version. Use relevant metrics and visualisations to aid your findings.
• Challenges and Limitations: Be honest about the challenges you encountered during the project and the limitations of your model. Discuss potential areas for improvement and future work.
• Version Control (Optional): Consider the use of a model manage system like Git to song changes made to your code and documentation over time. This may be helpful for collaboration and keeping a easy document of your challenge’s improvement.

By completing those initiatives and following pointers within the displays and documentation, you’ll gain precious enjoy for the duration of records technological know-how workflow.Please keep in mind the keys to showcase your passion for facts technology, your trouble-solving competencies, and your potential to examine and adapt. This will assist you to stick out from the gang and make a good influence on capacity employers.

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Pathways Study Genotype Data, Alliance A011502 Secondary Analysis Headline Roswell Park ASCO24 Presentations

Breast cancer experts Dr. Arya Roy and Dr. Shipra Gandhi to give invited talks at ASCO Annual Meeting 2024

New insights on improving clinical outcomes and quality of life among breast cancer patients highlight the slate of new research presentations Roswell Park Comprehensive Cancer Center experts will deliver at the American Society of Clinical Oncology (ASCO) Annual Meeting at McCormick Place in Chicago next week.

“We are extremely proud of the great work done by our researchers, who will present results from trials and new data on prognostic biomarkers, quality of life and the impact of stress on outcomes,” says  Renuka Iyer, MD , Vice Chair of Faculty Recruitment & Retention and Professor of Oncology in the Department of Medicine. 

Two physician-scientists from Roswell Park’s Breast Cancer Medical Oncology team will give invited talks on original research during the gathering of global oncology experts, patients and patient advocates, which begins Friday, May 31.

Arya Mariam Roy, MBBS , Hematology/Oncology Fellow, Class of 2024, will present “International medical graduates (IMG) representation at international oncology conference meetings” ( Abstract 9000 ), as part of a Clinical Science Symposium on Conflicts (of Interest) and Conundrums: Perspectives from the Global Oncology Community, Saturday, June 1, 1:15-2:45 p.m. CDT in S100bc, highlighting the differences in speaking opportunities for foreign medical graduates compared to graduates of U.S. medical schools. “This is very important as we strive for equity in our professional societies,” notes Dr. Iyer. 

Dr. Roy, who received an ASCO Annual Meeting Merit Award recognizing the high quality of her work, will also give a second oral presentation, “Breast cancer polygenic risk score and patient survival outcomes in the Pathways study” ( Abstract 10502 ) during the Prevention, Risk Reduction, and Genetics Oral Abstract session on Saturday, June 1, from 3-6 p.m. CDT in S100a. Based on the Pathways Study carried out in collaboration with Kaiser Permanente Northern California, the presentation reports findings of genome-wide genotype data for nearly 4,000 women. “This insightful application of polygenic scores is an important piece of data that has too often been missing in survivorship care, and tells us in a very well-done study the value the score has to predict second cancers and survival,” says Dr. Iyer.

Also speaking during the meeting will be  Shipra Gandhi, MD, MS , Associate Professor of Oncology in the Department of Medicine, who will highlight the findings of “Association of higher baseline stress and pain with clinical outcomes: Secondary analysis from Alliance A011502” ( Abstract 11016 ) during the Quality Care/Health Services Research Rapid Oral Abstract session on Monday, June 3, from 1:15-2:45 p.m. CDT in S102. “This is the first prospective study to show that higher stress and pain levels correlate with poor survival in breast cancer, underscoring the importance of managing these common symptoms in our patients,” says Dr. Iyer. 

Roswell Park Chief of Leukemia  Eunice Wang, MD , is Co-Chair and moderator of the  Hematologic Malignancies – Leukemia, Myodysplastic Syndromes, and Allotransplant Oral Abstract session, happening Friday, May 31, from 2:45-5:45 p.m. CDT in S100bc. And And Rohit Gosain, MD , Roswell Park faculty member and Medical Director of Roswell Park Hematology Oncology Southtowns, will be a panelist on a Trainee & Early Career Lounge Discussion “Leveraging Social Media Early on in Your Career” on Friday, May 31, from 2-2:45 p.m. CDT, Hall C (adjacent to Meeting Registration). 

Other featured abstracts

Thirteen teams will present new Roswell Park-led research during poster sessions at the ASCO 2024 Annual Meeting:

• Yu Fujiwara, MD , Hematology/Oncology Fellow in Roswell Park’s Department of Medicine, is first author on “Pan-cancer B- and T-cell transcriptome analysis of CXCL13 as a predictive marker for immune checkpoint inhibitor response,” to be presented during the Developmental Therapeutics – Immunotherapy session,  Abstract 2626 , poster board 105, Saturday, June 1, 9 a.m. to noon CDT in Hall A. Dr. Fujiwara is also senior author on “Surgical outcomes in patients with non-small cell lung cancer receiving neoadjuvant chemoimmunotherapy versus chemotherapy alone: A systematic review and meta-analysis,” to be presented during the Lung Cancer—Non-Small Cell Local-Regional/Small Cell/Other Thoracic Cancers session,  Abstract 8020 , poster board 282, Monday, June 3, 1:30-4:30 p.m. CDT in Hall A.
• Igor Puzanov, MD, MSCI, FACP , Senior Vice President of Clinical Investigation, The Judith and Stanford Lipsey Endowed Chair in Clinical Cancer Research, Professor of Oncology and Director of Early Phase Clinical Trials, Department of Medicine, is senior author on “A phase 1/1b study of the IL-2 prodrug WTX-124 in patients with locally advanced or metastatic solid tumors after checkpoint inhibitor therapy: Initial results of the combination dose escalation with pembrolizumab” ( Abstract 2623 ), to be presented in the Developmental Therapeutics—Immunotherapy session, poster board 102, Saturday, June 1, 9 a.m. – noon CDT in Hall A.
• Riya Jayesh Patel, MBBS , Hematology/Oncology Fellow in the Department of Medicine, is first author and  Renuka Iyer, MD , Vice Chair of Faculty Recruitment & Retention, is senior author on “Genomic signature analysis and survival outcomes in cholangiocarcinoma (CCA) using oncology research information exchange network (ORIEN) database,” to be presented in the Gastrointestinal Cancer – Gastroesophageal, Pancreatic, and Hepatobiliary session,  Abstract 4101 , poster board 81, Saturday, June 1, 1:30-4:30 p.m. CDT in Hall A.
• Deepak Vadehra, DO , Assistant Professor of Oncology and Co-Leader of the Adolescent and Young Adult Translational Research Group, Department of Medicine/Gastrointestinal Center, is first author and  Sarbajit Mukherjee, MD, MS , Co-Leader of GI Translational Research and Associate Professor of Oncology, Departments of Medicine and Immunology, is senior author on “Non-colorectal GI malignancies in the young: Incidence trends, demographic disparities, and survival analysis,” to be presented in the Gastrointestinal Cancer – Gastroesophageal, Pancreatic, and Hepatobiliary session,  Abstract 4023 , poster board 3, Saturday, June 1, 1:30-4:30 p.m. CDT in Hall A.
• Malak Saud Alharbi, MBBS , Hematology/Oncology Fellow in Roswell Park’s Department of Medicine, is first author and  Saby George, MD, FACP , Professor of Oncology and Medicine and Director of Network Clinical Trials, is senior author on “Impact of obesity on immune-related adverse events and tyrosine kinase inhibitor side effects in patients with metastatic renal cell carcinoma (mRCC),” to be presented during the Genitourinary Cancer – Kidney and Bladder session,  Abstract 4560 , poster board 255, Sunday, June 2, 9 a.m. to noon CDT in Hall A.
• Saby George, MD, FACP , Professor of Oncology and Medicine and Director of Network Clinical Trials, will present “Health-related quality of life (HRQoL) with nivolumab (NIVO) subcutaneous (SC) or intravenous (IV) in patients (pts) with advanced or metastatic clear cell renal cell carcinoma (ccRCC) who have received prior therapy in the phase 3 CheckMate 67T trial,” during the Genitourinary Cancer – Kidney and Bladder session,  Abstract 4535 , poster board 230, Sunday, June 2, 9 a.m.-noon CDT, in Hall A.

Mody Amin, MD, DO, Resident Physician with the Department of Medicine, is first author and  Eunice Wang, MD , is senior author on “Impact of body mass index and karyotype on clinical outcomes in adolescents and young adults (AYA) with acute myeloid leukemia,” to be presented in the Hematologic Malignancies – Leukemia, Myodysplastic Syndromes, and Allotransplant session,  Abstract 6551 , poster board 110, Monday, June 3, 9 a.m.–noon CDT in Hall A.

Dr. Amin is first author and  Francisco Hernandez-Ilizaliturri, MD , Director of Lymphoma Research and Professor of Oncology in the Department of Medicine, is senior author on “Carfilzomib plus rituximab, ifosfamide, carboplatin and etoposide (C-RICE) led to higher response, OS, and PFS in patients with transplant-eligible relapsed or refractory (R/R) diffuse large B-cell lymphoma (DLBCL)” poster in the Hematologic Malignancies – Lymphoma and Chronic Lymphocytic Leukemia session,  Abstract 7042 , poster board 25, Monday, June 3, 9 a.m.-noon CDT in Hall A.

• Muhammad Salman Faisal, MBBS , Hematology/Oncology Fellow in Roswell Park’s Department of Medicine, is first author and  Saby George, MD, FACP , Professor of Oncology and Medicine and Director of Network Clinical Trials, is senior author on “Risk assessment of cardiovascular adverse events with BTK inhibitors in hematological malignancies: Insights from FAERS,” to be presented during the Symptom Science – Palliative Care session,  Abstract 12145 , poster board 274, Monday, June 3, 1:30-4:30 p.m. CDT in Hall A.
• Amy Gallagher, PsyD, MSHCT , Director, Employee Resiliency Program, is first author and  Amy Case, MD , Chief Wellness Officer, is senior author on “Utilizing data to drive solutions for healthcare worker wellbeing,” during the Medical Education and Professional Development session,  Abstract 9012 , poster board 1, Monday, June 3, 1:30-4:30 CDT in Hall A.

Karan Jatwani, MD , Hematology/Oncology Fellow in Roswell Park’s Department of Medicine, is first author on “End-of-life care preferences in patients with gallbladder cancer: Shifting patterns and disparities over two decades,” to be presented during the Symptom Science – Palliative Care session,  Abstract 12036 , poster board 165, Monday, June 3, 1:30-4:30 p.m. in Hall A.

Dr. Jatwani is also first author on, and  Dharmesh Gopalakrishnan, MD , Assistant Professor of Oncology in the Department of Medicine/Genitourinary Center, is senior author on “Risk assessment of myelosuppression with PARP inhibitors in prostate cancer: Insights from FAERS” during the Symptom Science – Palliative Care session,  Abstract 12144 , poster board 273, Monday, June 3, 1:30-4:30 p.m. in Hall A.

Clinical Trials in Progress

Additionally, three Roswell Park teams will update their international colleagues on clinical trials that are currently underway:

• Robert Fenstermaker, MD , Chair of Neurosurgery, is senior author on "A multicenter, randomized controlled phase 2b trial of survivin vaccine SurVaxM plus adjuvant temozolomide for newly diagnosed glioblastoma (SURVIVE)" ( Abstract TPS2099 ), to be presented by Manmeet Singh Ahluwalia of Miami Cancer Institute during the Central Nervous System Tumors session, poster board 393a, Saturday, June 1, 11:30 a.m.-1 p.m. CDT in Hall A.  
• Christos Fountzilas, MD , Associate Director for Solid Tumors/Early Phase Clinical Trials Program, Associate Professor of Oncology and Co-Leader, Gastrointestinal Clinical Disease Team, Department of Medicine, is first author on “A randomized, multi-center, phase 2 study of ivaltinostat (Ival) plus capecitabine (Cape) versus capecitabine alone in the maintenance setting in patients with metastatic pancreatic adenocarcinoma (mPDAC)” ( Abstract TPS4206 ), to be presented in the Gastrointestinal Cancer – Gastroesophageal, Pancreatic, and Hepatobiliary session, poster board 173a, Saturday, June 1, 1:30-4:30 p.m. CDT in Hall A.
• Shipra Gandhi, MD, MS , Associate Professor of Oncology in the Department of Medicine, is first author and  Elizabeth Repasky, PhD , Vice Chair, Distinguished Member, Professor of Oncology and The Lawrence J. Minet Endowed Chair in Immunology, Department of Immunology, is senior author on “A phase II trial to assess the impact of ?2 adrenergic blockade in immune checkpoint inhibitor (ICI)– refractory metastatic triple negative breast cancer (mTNBC)” ( Abstract TPS1141 ), to be presented during the Breast Cancer – Metastatic session, poster board 108b, Sunday, June 2, 9 a.m.-noon CDT in Hall A.

Medical Disclaimer

Calliditas Therapeutics Presents Data at the 61[st] European Renal Association Congress

Calliditas Therapeutics AB (Nasdaq: CALT, Nasdaq Stockholm: CALTX) (“Calliditas”), today announced the presentations of an additional efficacy analysis of Nefecon (TARPEYO® (budesonide) delayed release capsules)) as well as a real-world analysis of the use of systemic glucocorticoids (SGC) in IgA nephropathy (IgAN). These were presented at ERA 2024 virtually and in Stockholm on May 23 – 26, 2024.

The presented efficacy analysis of Nefecon and sparsentan showed that treatment with Nefecon for 9 months was associated with estimated glomerular filtration rate (eGFR) benefit compared with continuous treatment with sparsentan.

Additionally, the findings of a real-world analysis of challenges associated with the use of systemic glucocorticoids demonstrate significant side effects and costs for IgAN patients treated with systemic glucocorticoids (SGC), such as Prednisone and Prednisolone.

“It was wonderful to participate in ERA 2024 and present data contributing to the discussion on the need for effective treatments in IgAN,” said Richard Philipson, Chief Medical Officer of Calliditas, “ We continue to gather evidence that highlights the importance of treating the underlying autoimmune pathogenesis associated with IgAN, and we believe TARPEYO, as the only approved immunomodulating therapy designed to target the production of Gd-IgA1, has the potential to become a cornerstone therapy in IgAN.”

Poster presentation details are below and will be available on the Presentations and Publications page on the Calliditas’ corporate website following the meeting.

Presentation Analyses:

Title: “Matching-adjusted indirect comparison of eGFR in patients with immunoglobulin A nephropathy treated with Nefecon (TRF budesonide) or sparsentan”

A matching-adjusted indirect comparison (MAIC) methodology is a widely accepted and relevant methodology for comparing treatments across trials in the absence of head-to-head comparisons. Here the effects of Nefecon, marketed as TARPEYO® and sparsentan, marketed as FILSPARI™, on kidney function deterioration in patients with IgAN were compared, as assessed by eGFR change from baseline at 9, 12 and 24 months. Results from the MAIC showed significantly favorable effects of Nefecon versus sparsentan on eGFR across all time points analyzed. Mean differences in the absolute change in eGFR of 5.68mL/min/1.73 m2 (95% credible interval [Crl] 3.14, 8.20; p<0.001), 3.48 mL/min/1.73 m2 (95% Crl 0.97, 5.97; p=0.006) and 3.28 mL/min/1.73 m2 (95% Crl 0.02, 6.51; p=0.048) were observed when comparing Nefecon with sparsentan at 9 months vs 36 weeks, 12 months vs 48 weeks, and 24 months vs 106 weeks, respectively. This efficacy analysis showed that treatment with Nefecon 16 mg/day for 9 months was associated with greater eGFR benefit compared with continuous treatment with sparsentan 400 mg/day over 2 years, with significant differences observed as early as 9 months after treatment initiation and sustained up to 2-years of follow-up. While the rigor of well-controlled head-to-head clinical trials cannot be replicated, MAIC is also a widely accepted and relevant methodology for comparing treatments across trials in the absence of head-to-head comparisons 1,2, *

Title: “Real-world challenges associated with the use of systemic glucocorticoids in a US IgAN cohort”

Per Kidney Disease: Improving Global Outcomes (KDIGO) guidelines, patients at high risk of progressive chronic kidney disease despite maximal supportive care can be considered for a 6-month course of systemic glucocorticoids (SGC), although important risks of toxicity and contraindications must be considered. There is currently limited real-world evidence describing the impact of the use of SGC on treatment‑emergent toxicity and healthcare resource utilization (HCRU) in patients with IgAN. Our findings demonstrate significant side effects and costs for IgAN patients treated with SGC compared with patients not treated with SGC. Increases in severe infection incidents, inpatient visits, emergency department admissions, and ambulatory visits, underscore the careful consideration of treatment-emergent toxicity prior to initiating SGC therapy in patients with IgAN.

• * The optimization strategy in NefIgArd (optimized RASi) differed from the optimization strategy in PROTECT (IR), and anchoring of the two trials at optimized RASi/IR might lead to biased results. However, we also evaluated an unanchored MAIC in a sensitivity analysis and found very similar results.
• The MAIC method can only adjust the relative effect estimates for any observed effect modifier available in the data, but it cannot adjust for unobserved or unobservable effect modifiers. A significant number of potential treatment effect modifiers were included in the present analysis: age, sex, race, baseline eGFR, UPCR, UACR, and urinary protein excretion.

TARPEYO is indicated to reduce the loss of kidney function in adults with primary immunoglobulin A nephropathy (IgAN) who are at risk for disease progression.

Important Safety Information

Contraindications: TARPEYO is contraindicated in patients with hypersensitivity to budesonide or any of the ingredients of TARPEYO. Serious hypersensitivity reactions, including anaphylaxis, have occurred with other budesonide formulations.

Warnings and Precautions

Hypercorticism and adrenal axis suppression: When corticosteroids are used chronically, systemic effects such as hypercorticism and adrenal suppression may occur. Corticosteroids can reduce the response of the hypothalamus-pituitary-adrenal (HPA) axis to stress. In situations where patients are subject to surgery or other stress situations, supplementation with a systemic corticosteroid is recommended. When discontinuing therapy or switching between corticosteroids, monitor for signs of adrenal axis suppression.

Patients with moderate to severe hepatic impairment (Child-Pugh Class B and C respectively) could be at an increased risk of hypercorticism and adrenal axis suppression due to an increased systemic exposure to oral budesonide. Avoid use in patients with severe hepatic impairment (Child-Pugh Class C). Monitor for increased signs and/or symptoms of hypercorticism in patients with moderate hepatic impairment (Child-Pugh Class B).

Risks of immunosuppression: Patients who are on drugs that suppress the immune system are more susceptible to infection than healthy individuals. Chickenpox and measles, for example, can have a more serious or even fatal course in susceptible patients or patients on immunosuppressive doses of corticosteroids. Avoid corticosteroid therapy in patients with active or quiescent tuberculosis infection; untreated fungal, bacterial, systemic viral, or parasitic infections, or ocular herpes simplex. Avoid exposure to active, easily transmitted infections (e.g., chicken pox, measles). Corticosteroid therapy may decrease the immune response to some vaccines.

Other corticosteroid effects: TARPEYO is a systemically available corticosteroid and is expected to cause related adverse reactions. Monitor patients with hypertension, prediabetes, diabetes mellitus, osteoporosis, peptic ulcer, glaucoma or cataracts, or with a family history of diabetes or glaucoma, or with any other condition where corticosteroids may have unwanted effects.

Adverse reactions: In clinical studies, the most common adverse reactions with TARPEYO (occurring in ≥5% of TARPEYO treated patients, and ≥2% higher than placebo) were peripheral edema (17%), hypertension (12%), muscle spasms (12%), acne (11%), headache (10%), upper respiratory tract infection (8%), face edema (8%), weight increased (7%), dyspepsia (7%), dermatitis (6%), arthralgia (6%), and white blood cell count increased (6%).

Drug interactions: Budesonide is a substrate for CYP3A4. Avoid use with potent CYP3A4 inhibitors, such as ketoconazole, itraconazole, ritonavir, indinavir, saquinavir, erythromycin, and cyclosporine. Avoid ingestion of grapefruit juice with TARPEYO. Intake of grapefruit juice, which inhibits CYP3A4 activity, can increase the systemic exposure to budesonide.

Use in specific populations

Pregnancy: The available data from published case series, epidemiological studies, and reviews with oral budesonide use in pregnant women have not identified a drug-associated risk of major birth defects, miscarriage, or other adverse maternal or fetal outcomes. There are risks to the mother and fetus associated with IgAN. Infants exposed to in-utero corticosteroids, including budesonide, are at risk for hypoadrenalism.

Please see Full Prescribing Information .

About TARPEYO

TARPEYO is an oral 4mg delayed release formulation of budesonide, designed to remain intact until it reaches the ileum. Each capsule contains coated beads of budesonide that target mucosal B-cells present in the ileum, including the Peyer’s patches, which are responsible for the production of galactose-deficient IgA1 antibodies (Gd-Ag1) causing IgA nephropathy.

About Primary Immunoglobulin A Nephropathy

Primary immunoglobulin A nephropathy (IgA nephropathy or IgAN or Berger’s Disease) is a rare, progressive, chronic autoimmune disease that attacks the kidneys and occurs when galactose deficient IgA1 is recognized by autoantibodies, creating IgA1 immune complexes that become deposited in the glomerular mesangium of the kidney. This deposition in the kidney can lead to progressive kidney damage and potentially a clinical course resulting in end- stage renal disease. IgAN most often develops between late teens and late 30s.

For further information, please contact:

Åsa Hillsten, Head of IR & Sustainability, Calliditas

Tel.: +46 76 403 35 43, Email: asa.hillsten@calliditas.com

The information was sent for publication, through the agency of the contact persons set out above, on May 28, 2024, at 14.00 p.m. CET.

• CALT_ERA Data Release_ENG

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Decoding Microsoft’s YouTube Advertising Strategy in Q1 2024

All the vital news, analysis, and commentary curated by our industry experts.

Published: May 27, 2024 Report Code: GDSM-SA-0018-ST

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Table of Contents

The report on Microsoft's advertising strategies on YouTube during the first quarter of 2024, focuses on key products such as Microsoft Copilot and its integration with post meeting recaps and PowerPoint presentations, followed by collaboration between Microsoft Azure Quantum and PNNL. It analyzes the core themes, messaging strategies, and product benefits portrayed in these advertisements, highlighting elements such as AI Integration, Time Management, Personalization and Collaboration. Moreover, the report examines the overarching themes of Innovation, Efficiency, Sustainability and Empowerment infused into these campaigns. By synthesizing these insights, the report aims to provide a nuanced understanding of Microsoft's successful YouTube advertising tactics and their impact during the initial quarter of 2024.

This report delves into Microsoft's dominant YouTube advertising campaigns during Q1 2024, with the major share of 40% dedicated to Educational Ads and 30% dedicated to Tutorial Ads. The advertisements meticulously highlight key values such as AI-Powered Assistance, Achievability, and Collaboration. They portray the transformative capabilities of the product, illustrating how it turns ideas into action and achieves seemingly impossible tasks. Visual representations effectively demonstrate features and benefits, while leveraging the company's brand reputation reinforces its value proposition. Effortless integration into daily routines is emphasized, ensuring enhanced productivity without disruption. Reduction of lithium dependency and promotion of battery innovation underscore the company's commitment to sustainability. Initiatives aimed at accelerating discovery processes and integrating sports and STEM education highlight collaborative efforts, urging viewers to participate in shaping a better future.

• Product Focus: Investigate how Microsoft positions its flagship products (Microsoft Copilot) within the YouTube ads, analyzing the emphasized features and benefits.

Reasons to Buy

• By examining Microsoft's advertising strategies, brands can benchmark their own performance against a leading industry competitor, gaining valuable insights into areas of strength and opportunities for improvement.

Advertisements and their Tones

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