Data science news

Data Visualization: Your Secret Weapon in Storytelling and Persuasion 

In a world in­creas­ingly sat­ur­ated with data and in­form­a­tion, visu­al­iz­a­tions are a po­tent way to break through the clut­ter, tell your story, and per­suade people to ac­tion. Raw stat­ist­ics by them­selves are fine. But show­ing in con­text, wheth­er with a sim­ple chart or more cre­at­ively in an in­ter­act­ive form, is the fu­ture of shar­ing in­form­a­tion, and needs to be em­bed­ded in the think­ing of all com­mu­nic­a­tions pro­fes­sion­als. Combining data – which can be dry – with real cre­ativ­ity – which isn’t some­thing hu­mans, even cre­at­ive ones, can simply turn on and off – can be chal­len­ging. Yet we live in a stream-powered mo­bile world that is in­creas­ingly visu­al, in­spir­ing de­mands from me­dia to achieve equal parts style and sub­stance for news. This ex­plains why unique and truly com­pel­ling visu­al­iz­a­tions are an un­der­used, yet dev­ast­at­ingly ef­fect­ive tac­tic. They are equal parts rare and in de­mand. They beg to be shared. They are a cata­lyst for con­ver­sa­tion, aware­ness, and ac­tion.

Blending Data and Visualization for Better Revenue

The need for data is not new for busi­nesses.

They have been at­tempt­ing to ac­cu­mu­late data for many years to help them know how to in­crease rev­en­ue, im­prove profits or bet­ter ap­peal to cus­tom­ers. New tech­no­lo­gies have made it easi­er to col­lect that data and now to use it dif­fer­ent ways.

Blending data and us­ing visu­al­iz­a­tion is provid­ing more in­form­a­tion for busi­nesses to be more com­pet­it­ive.

Data Blending is the Key to Analysis Data blend­ing and visu­al­iz­a­tion work to­geth­er to give com­pan­ies a bet­ter look at their op­tions and op­por­tun­it­ies. It can be used in many dif­fer­ent ways to de­term­ine how be­st to pro­ceed. For ex­ample, an or­gan­iz­a­tion can de­term­ine how the res­ults will dif­fer with a com­pleted pro­ject if it were to be at­temp­ted with new data. Instead of just plug­ging in pro­jec­ted num­bers and guess­ing what dif­fer­ence they would make, data blend­ing al­lows com­pan­ies to see the dif­fer­ences in the pro­cesses and get the de­tails for why the res­ults are dif­fer­ent.

Predictive Analytics: Staying Ahead of Your Customers 

Can a re­l­at­ively ma­ture tech­no­logy help con­tent pub­lish­ers and mar­keters make web­site vis­it­ors more sticky and al­low them to re­tain di­git­al sub­scribers while also rais­ing prices? The an­swer is yes.

The sci­ence be­hind what is mak­ing the afore­men­tioned pos­sible – pre­dict­ive ana­lyt­ics – has been around for quite awhile. In its former life, it was known as data min­ing. Add in Big Data and the rap­idly matur­ing tech­no­logy looks as if it’s ready for its close-up.

PREDICTIVE ANALYTICS 101

Predictive ana­lyt­ics (PA) “de­scribes a range of ana­lyt­ic­al and stat­ist­ic­al tech­niques used for de­vel­op­ing mod­els that may be used to pre­dict fu­ture events or be­ha­vi­ors,” as defined by Techopedia. It’s been suc­cess­fully em­ployed in many in­dus­tries, in­clud­ing bank­ing, tele­comm, and health­care.

Data Literacy — What It Is And Why None of Us Have It 

With all the talk about big data, one thing is very clear: the vast ma­jor­ity of us have very little in­sight in­to how to ac­tu­ally find in­sight in it. We have neither strategies nor ex­per­i­ence, mostly be­cause the use of data at scale is re­l­at­ively new. Sure, hu­mans have been us­ing data for thou­sands of years to tell stor­ies, pass along ideas, re­cord his­tory and, in more mod­ern times, pro­duce ROI and elim­in­ate func­tions with high spend and low re­turn.

But, big data is un­like data of the past. Not ne­ces­sar­ily in its use. Data cer­tainly still tells stor­ies, passes along ideas, re­cords his­tory, pro­duces ROI and saves money. But its sheer size makes it com­pletely dif­fer­ent than any data set hu­man­ity has man­aged to date.

We are no longer work­ing with a Rosetta Stone size of in­form­a­tion (neither the ac­tu­al stone nor the mod­ern day disks), or even spread­sheets of data that can in turn be put in­to a semi-useful pivot chart. We are deal­ing with massive, and I re­peat massive, scales of data. Umbel’s Digital Genome alone col­lects, ana­lyzes and visu­al­izes 18,446,744,073,709,600,000 data point­sper per­son in less than one second.

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