Data Visualization & It's Importance !!

Data visualization is the presentation of data in a pictorial or graphical format. It enables decision makers to see analytics presented visually, so they can grasp difficult concepts or identify new patterns. With interactive visualization, you can take the concept a step further by using technology to drill down into charts and graphs for more detail, interactively changing what data you see and how it’s processed.

Why Visualization?

Do you think giving you the data of lets say 10 Million points in a Database file and asking you to provide your inferences by just seeing the data on that table is feasible? This is when we make use of Data visualization, wherein all the data will be transformed into some form of plots and analyzed further from that. As being a human, we are more used to grasp a lot of info from diagrammatic representation than the counterparts.

Why is data visualization important?

Because of the way the human brain processes information, using charts or graphs to visualize large amounts of complex data is easier than poring over spreadsheets or reports. Data visualization is a quick, easy way to convey concepts in a universal manner – and you can experiment with different scenarios by making slight adjustments.

Data visualization can also:

·      Identify areas that need attention or improvement.

·      Clarify which factors influence customer behavior.

·      Help you understand which products to place where.

·      Predict sales volumes.

THE IMPORTANCE OF DATA VISUALIZATION 

1. ABSORB INFORMATION QUICKLY.

A picture is worth a thousand words. Or, in this case, a picture is worth thousands of lines of data. As data volume inevitably increases, visualization manages influxes of new information and makes it easy to find trends.

2. UNDERSTAND YOUR NEXT STEPS.

From these visual trends, you can easily understand your best next steps with less time and energy dedicated to data analysis. You can save hours of time by looking at the big picture instead of a thousand puzzle pieces.

3. HOLD YOUR AUDIENCE’S INTERESTS LONGER.

Graphics built with your data replay a message quickly, before you lose interest. As people now have an attention span shorter than that of goldfish, keeping interest is a crucial goal when sharing insights.

5. KICK THE NEED FOR DATA SCIENTISTS.

Data visualization makes data more accessible and less confusing. Just years ago, the only professionals who could understand company data worked in the IT department. Now, finance, sales, and marketing teams not only have an avid interest in what they’re data tells them, but they have the means to actually go after the answers.

6. SHARE YOUR INSIGHTS WITH EVERYONE.

It makes data more shareable. Visualizations can be distributed among teams easily, and your teams will be much more receptive to an attractive visual than a massive Excel spreadsheet.

7. FIND THE OUTLIERS.

Data visualization quickly reveals the outliers in your data. As outliers tend to drag down data averages in the wrong direction, it’s crucial to find and eliminate them from your analysis when they skew the results. Graphics quickly shed light on them, allowing you to understand why they’re there and ignore them when necessary.

8. ACT ON YOUR FINDINGS QUICKLY.

Most importantly, data visualization allows you to make decisions faster. Using them, you can review your strategies quickly and make updates efficiently, helping you achieve success with fewer mistakes and greater speed.

9. IT ANSWERS SPECIFIC QUESTIONS.

You analyze data, because you have questions. You make data visualizations because you want to get to these answers faster. If you skip that crucial first step, your graphics serve no purpose.

10.IT’S USER-FRIENDLY.

Data visualizations shouldn’t exist in a vacuum. The best visuals can be quickly and easily updated with new data to keep analysis fresh and ongoing. You shouldn’t have to build from the ground up every time.

11. IT TELLS A VISUAL STORY.

Remember, graphics rose in popularity because they simplify a complicated message. You turn to data visualization when there’s too much data to follow with words. Make sure your visualization conveys the message in an easily-understood way. It should tell a story.