{"id":4449,"date":"2019-03-07T17:17:38","date_gmt":"2019-03-07T22:17:38","guid":{"rendered":"https:\/\/solutionsreview.com\/business-intelligence\/?p=4449"},"modified":"2019-03-12T09:44:59","modified_gmt":"2019-03-12T13:44:59","slug":"three-crucial-steps-towards-data-visualization-success","status":"publish","type":"post","link":"https:\/\/solutionsreview.com\/business-intelligence\/three-crucial-steps-towards-data-visualization-success\/","title":{"rendered":"Three Crucial Steps Towards Data Visualization Success"},"content":{"rendered":"

\"Three<\/p>\n

This article is a part of Solutions Review’s Best Practices Series, a collection of insights from industry experts and practitioners in the field, providing perspective that we hope can help you in your search for the best data analytics and BI software<\/a>.<\/em><\/span><\/p>\n

By Josh Jones<\/strong><\/em><\/p>\n

Have you ever heard the adage, \u201cyou first eat with your eyes?\u201d Beautiful food is more appetizing, which is why fancy restaurants spend so much time making their meals more visually appealing. Data is no different. Displaying it visually can do wonders for getting your point across. That\u2019s what data visualization is all about.<\/p>\n

Data Visualization Defined<\/strong><\/h2>\n

Data visualization means giving numbers a visual context, and extends existing concepts such as\u00a0business intelligence and analytics. Someone (wisely) decided that the interesting bits (outliers and trends) are better seen not as black and white numbers on a spreadsheet, but as graphics made of colors, lines and shapes.<\/p>\n

Textual Data Explanation\u00a0<\/strong><\/h3>\n

The business analyst examined 22 data points, noting that most followed a relatively strong linear trend. The analyst also noted that two of the data points did not conform to the trend. These were flagged for further analysis.<\/p>\n

Data Visualization<\/strong><\/p>\n

\"Data<\/p>\n

Which reporting format makes identifying data outliers easier?<\/strong><\/h3>\n

The point of visualizing data is to engage the user, deliver information faster, and otherwise enable business insight. As you read on, you\u2019ll notice that I use different terms (dashboards, reports, visuals, visual analytics, etc.).\u00a0 All of these refer to some sort of visual output based on data.<\/p>\n

Visual Analytics Done Well<\/strong><\/h3>\n

As a practitioner of data visualization for the past ten years, I can wholeheartedly endorse the importance of doing visualizations well. I\u2019ve seen good data viz get users excited about their data and engage senior management. Just this year, at a major client, my consulting company and I created a one-page KPI dashboard for an EVP. It only had about twelve numbers and focused on visuals rather than a wall of numbers. The dashboard was so well-received that directors and VPs sent me emails with their thanks. Success like that of course comes from hard work, starting with three major things to think about sooner rather than later. To set yourself up for success, here\u2019s what to do.<\/p>\n

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\"\"<\/a><\/p>\n<\/div>\n\t\t<\/div><\/div>\n

1. Plan and Organize before You Build<\/strong><\/h4>\n

Blueprints come before construction. Plan before you start building.<\/p>\n

One of those emails I mentioned above said \u201cthank you,\u201d followed by \u201cleadership would also like to see x, y and z.\u201d This brings up an important point. Once users see data visually, they want more. That means you have more reports, more requests to keep organized, and user expectations to manage.<\/p>\n

To get ahead of your users, resolve key questions and responsibilities as early as possible. For example:<\/p>\n