Data science news

When is data visu­al­iz­a­tion use­ful?

In or­der to know when data visu­al­iz­a­tion should be used, it’s a good idea to start with why we even use it at all, and what makes it work.

Why visu­al­ize data The whole point of tak­ing data and turn­ing it in­to more un­der­stand­able in­form­a­tion is so that we can util­ize it to make a de­cision or take ac­tion from what we learn. Data visu­al­iz­a­tion is just an­other way of turn­ing data that we can’t read or un­der­stand and turn­ing it in­to some­thing that we can see and use. In oth­er words, cre­at­ing in­form­a­tion with vis­ible in­sights.

In gen­er­al there are three reas­ons why you might want to visu­al­ize data:

1.Education – Many visu­al­iz­a­tions are valu­able be­cause they edu­cate or re­port on a spe­cific top­ic. These can also provide in­sight in­to changes re­lated to a top­ic over time, so that you are able to un­der­stand trends and learn from them.
2.Exploration – As more data sets be­come in­creas­ingly lar­ger, it can be tough to eas­ily spot re­la­tion­ships between them and cre­ate pre­dic­tions. Visualization can make this easi­er to un­der­stand and man­age.
3.Confirmation – If there are as­sump­tions about a sub­ject, and data has been col­lec­ted, visu­al­iz­ing it can be a use­ful way to prove or dis­prove the as­sump­tion.

Visualization: The Simple Way to Simplify Big Data

Data visu­al­iz­a­tion has an amaz­ing abil­ity to make the com­plex sim­ple, and the latest tools can do much more than give every­one the same view of data. It’s only through visu­al­iz­a­tion that we can take some­thing as ab­stract as sym­bols and turn it in­to a phys­ic­al im­age that has di­men­sions that our eyes can quickly see and our brains un­der­stand. We can grasp data’s mean­ing more quickly. Visualization tells us when trends are head­ing in the wrong dir­ec­tion and we need to in­ter­ve­ne.

But even more, when we visu­al­ize the scope and scale of today’s enorm­ous data sets, we pick up things with the na­ked eye that would oth­er­wise be hid­den. We can see data’s pre­vi­ously un­told story. We can see where Pennsylvania’s Vote ID Law is dis­pro­por­tion­ately af­fect­ing minor­it­ies and stu­dents. Visualization of Twitter data can show us a re­volu­tion as it un­folds in Cairo. What was be­ing re­por­ted in the me­dia as mass crowds form­ing in Tahrir Square comes to life when the net­work data be­comes visu­al­ized as it grows.

Big Data Analysis Vs. Government Spending

Federal IT pro­fes­sion­als es­tim­ate that gov­ern­ment agen­cies po­ten­tially can save 14% of their budgets, or nearly $500 bil­lion across the gov­ern­ment, from suc­cess­fully ana­lyz­ing big data. But while nearly one-fourth of fed­er­al IT man­agers in a new gov­ern­ment poll re­port their agen­cies have launched at least one big-data pro­ject, only 31% be­lieve their agency’s big-data strategy is suf­fi­cient to de­liv­er on that po­ten­tial.

The num­bers come from a re­cent re­port, “Smarter Uncle Sam: The Big Data Forecast,” by gov­ern­ment IT net­work­ing group MeriTalk. The re­port, sponsored by EMC Corporation, is based on a sur­vey of 150 fed­er­al IT pro­fes­sion­als.

How Financial Institutions Can Benefit from Predictive Analytics.

It’s an en­dur­ing busi­ness chal­lenge: How do you raise cus­tom­er sat­is­fac­tion and in­crease prof­it­ab­il­ity in a ma­ture, sat­ur­ated, and highly reg­u­lated in­dustry? Traditional solu­tions fo­cus on in­cre­ment­al ef­forts around the edges — pri­cing of­fers, pro­duct tweaks, and payroll cuts. These have of­ten led to poor cus­tom­er ser­vice and un­prof­it­able dis­count­ing.

A dif­fer­ent ap­proach, based on proven ana­lyt­ic tech­no­lo­gies, sup­ports more pos­it­ive and sus­tain­able out­comes. Customer ser­vice, with mil­lions of in­ter­ac­tions each day, is the lo­gic­al place to im­ple­ment this ap­proach.

Advances in pre­dict­ive ana­lyt­ics give fin­an­cial in­sti­tu­tions (FIs) a much deep­er un­der­stand­ing of their cus­tom­ers’ needs, sen­ti­ments, and be­ha­vi­ors. Equipped with bet­ter in­sights, FIs can im­ple­ment highly ac­cur­ate mod­el­ing cap­ab­il­it­ies to im­prove the cus­tom­er ex­per­i­ence at every con­tact. Furthermore, in­teg­rat­ing ana­lyt­ics and mod­el­ing in­to busi­ness op­er­a­tions sus­tains prof­it­ab­il­ity and cus­tom­er sat­is­fac­tion over the long term.

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