Big Data

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Data Visualization Storyboard: Documenting Goals

Gaining a clear understanding of your audience's goals and existing pain points will help you determine what to include and — more importantly — what not to include in the storyboard. The easiest way to [more…]

Data Visualization Storyboard: Documenting Key Performance Indicators (KPIs)

Understanding the key measurements that your audience must view, monitor, or track is the last step in developing your story. In simple terms, a key performance indicator [more…]

Building Data Visualization for Mobile

Let's face it: If you're not thinking mobile, you're probably in the wrong industry. Smartphones and tablets have forever changed the way that humans expect to interact with applications. The iTunes and [more…]

Important Statistical Formulas for Big Data

The word statistics may evoke fear in some beginners to data visualization, but if you ignore this topic, you overlook one of the most powerful ways to derive true insight and value from Big Data. [more…]

Understanding the Difference between Data Visualization and Infographics

To simplify the process of understanding visualizations, you should know the two most popular types: data visualizations and infographics. Because the use of graphical data visualizations is growing quickly [more…]

Data Visualization Storyboard: Identifying Your Audience

The first step in developing a clear storyboard for you data visualization is identifying your audience. Who you're building your data visualization for ultimately determines what kind of storyboard you [more…]

Top 10 Data Visualization Resources

To help you use data visualizations to help your data tell interesting stories and provide a competitive advantage, here are ten examples to look at for inspiration. You may want to bookmark the sites [more…]

User Engagement in the Data Visualization Development Process

If you build a data visualization, but it doesn't engage the interest of your audience, all your work is for naught. User engagement throughout the development process is the key to success. [more…]

Data Visualization: Examples of the Good and the Bad

It's easy to look at data visualizations in a superficial way and just enjoy the effect of the visuals. Some visualizations are dazzlingly interactive; others are funny or clever. But when it comes to [more…]

Data Visualization: Developing a Simple Black-and-White Mock-Up

After you've done the hard work of defining and outlining your storyboard, it's time to develop your mock-up. Mock-ups are also referred to as wireframes [more…]

Data Visualization: Developing Your Mock-Up Using Pencil and Paper

Although software is available for doing just about everything, including drawing your data visualization mock-ups, don't overlook the good old pencil-and-paper approach. It's as good now as it was in [more…]

Data Visualization: Building Template Layouts for Your Mock-Up

Whether you've chosen to use pencil and paper or a software mock-up tool, the good news is that you don't need to reinvent the wheel. Building and using templates is the quickest and smartest way to approach [more…]

Recognizing the Three Traits of an Effective Visual

When your black-and-white mock-up is complete, you're ready to add the oh-so-powerful visuals that will make it pop. That's why you started this journey to begin with, right? When adding visuals to your [more…]

Data Visualization: Developing Your Mock-Up with Web-Based or Desktop Tools

Although this market is still maturing, using a software-based tool to do your mock-up can be quite beneficial for several reasons: [more…]

Recognizing the Human Components of Data Visualization

Adding a component such as easy-to-use navigation, or choosing and applying an effective color scheme to data visualization is referred to as the human side of data viz. Humanizing your data viz a critical [more…]

Data Visualization: Adding Functionality

It's important to understand functionality in the data-viz world: a series of actions that you expect users to take, usually in a sequential manner, that helps them have the most optimal experience with [more…]

Data Visualization: Choosing Navigation by Using Rules

Imagine having a business that can't be found using one of the popular GPS systems, such as Google Maps. Revenue will suffer, and the business could fail. The same applies to a data visualization that [more…]

Data Visualization: Identifying the Most Popular Menu Types

Choosing the right menu type to ensure great navigation on your data visualization is more important than you may realize. Just think about how heavily dependent you are on menus to navigate your favorite [more…]

Data Visualization: Using Branding Guidelines to Choose a Color Scheme

One way to determine the right colors for your data visualization is to use the company branding guidelines — a document that many companies develop to ensure that materials produced by the company always [more…]

Data Visualization: Choosing a Color Scheme without Branding Guidelines

On the Internet, you can find software to do just about anything — even select your data visualization color scheme! In the event that you don't have access to a set of branding guidelines, you can use [more…]

Data Visualization: Understanding User Adoption

Getting a high user adoption rate for your data visualization (data viz for short) is your most important goal. Although this may seem obvious, user adoption [more…]

10 Ways to Market to Data Visualization Users

If you think that when you're done building your data visualization (data viz for short) that you can simply send an e-mail with the subject "The Sales Pulse app is now available [more…]

4 Common Fears of New Data Visualization Creators

As a beginner, it can be a bit overwhelming when you create your first data visualization (data viz for short). Tackling something new is always unsettling. Often, a lot is riding on producing a data viz [more…]

Building a Predictive Analytics Model

A successful predictive analytics project is executed step by step. As you immerse yourself in the details of the project, watch for these major milestones: [more…]

Data Sources for Predictive Analytics Projects

Data for a predictive analytics project can come from many different sources. Some of the most common sources are within your own organization; other common sources include data purchased from outside [more…]

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