Choosing the right data visualization tool is key to effectively communicating insights. This guide explores when to use infographics, data placemats, and dashboards, helping you simplify complex data, engage stakeholders, and enhance decision-making. Plus, download our free infographic for a quick reference!

Unlock the secrets to using pie charts effectively with this step-by-step article! Learn how to transform your data storytelling by avoiding common pitfalls, mastering design best practices, and ensuring your visualizations convey clear, impactful insights.

This article highlights common misuses of pie charts —like having too many categories or using 3D designs—and provides practical fixes to improve your visualizations. Learn how to enhance clarity, make accurate comparisons, and choose the right chart type for your data, ensuring your visuals effectively communicate your message. Don’t let poor chart design distort your data!

Slope charts are an effective data visualization tool for illustrating changes over time. They allow for easy comparisons between two distinct time periods, simplify complex data, and enhance data storytelling. This article provides a step-by-step guide on how to create an impactful slope chart in Excel, including best practices for formatting, highlighting key insights, and improving the overall appearance.

Discover our new Stratified Sampling Tool template, designed for researchers and evaluators working with large datasets. Learn how to generate representative samples, ensure fair subgroup representation, and increase precision in your data collection. Includes both single strata and multiple stratum versions with step-by-step instructions.

Explore the power of line charts in our ongoing series on data visualization. This article explains how to create impactful line charts using Excel 365. This tutorial not only guides you through chart creation but also emphasizes data visualization best practices to enhance clarity and professionalism. Whether you're new to charting or refining your skills, this article equips you with essential techniques for visually compelling data storytelling.

Enhance evaluation precision through Stratified Random Sampling—a method that partitions populations into subgroups for nuanced insights. Whether adopting proportionate or disproportionate approaches, this strategy fosters inclusivity and robust representation, enriching the evaluative process, learn about it in this article.

In this article, we'll show you an easy way to align y-axis labels in Excel charts and Microsoft applications. It's a simple but important step to make sure your data visualizations are clear and accurate.

Data protection in the world of evaluation is a must, especially when handling personally identifiable information (PII). Want to learn how to safeguard your data effectively? Discover the essential steps, including encryption and anonymization, to ensure your PII is shielded from unauthorized access, all while staying compliant with regulations.

While traditional bar charts are both straightforward and powerful for data representation, there are instances when we seek innovative alternatives to breathe new life into our reports. Enter the lollipop chart. Learn how to develop them in Excel here.

In this first instalment of our Data Visualization Applications series, we'll guide you through the art of transforming raw data into compelling visualizations. We kick things off by delving into the power and simplicity of the bar chart. By following these steps and best practices, you'll elevate your charts to ensure your data speaks clearly and convincingly. Stay tuned for more insights and techniques in our Data Visualization Applications series.

Want visuals that best express your data story? Here are some ideas to clean up those charts and help make them pop.

Chart templates will alleviate the pains of trying to reformat every new chart from scratch. From adjusting text size and font to formatting bar width and colour, a template will save you a significant amount of time in drafting your next evaluation report.

Bias in evaluation is inevitable. Reflection helps us to identify our bias and when we do, it is necessary to identify sources of bias in our processes, eliminate which bias we can, and acknowledge which bias we cannot.

For those interested in calculating sample sizes by hand, or getting a better understanding of the math behind many sample size calculators, we outline the formulae used to calculate sample sizes.

In this article, we briefly define sample sizes, their importance, and how to calculate them (or how to use a tool to calculate them).

If you work with data in Excel, whether frequently or infrequently, learning the basics of PivotTables will improve your ability to quickly explore and analyze raw data.

The end goal of collecting data is to eventually draw meaningful insights from said data. However, the transition from raw data to meaningful insights is not always a linear path. Data are prone to human-error and this guide will help you correct those errors, as well as provide tips on how to minimize these errors in the future.

As evaluators, we are rarely organizational decision-makers; it is our job to provide those decision-makers with actionable insights. In this article we highlight how you can translate data into meaningful findings, or insights, so you can support decision-makers to drive action within their organizations.

A tutorial on creating column charts in Microsoft Excel. Learn the basics of creating and transforming your column charts into something clean, informative, and impactful.