Tam­ing the Ele­phant

It is now time for cloud and big data to come to­gether


‘Big data’ refers to data sets whose size is be­yond the abil­ity of typ­i­cal data­base soft­ware tools to cap­ture, store, man­age, and an­a­lyze. As we know, tech­nol­ogy ad­vances over time there­fore the size of data sets that qual­ify as big data will also in­crease. It would vary as tech­nol­ogy ad­vances and also by sec­tor, depend­ing on the vol­ume and ve­loc­ity of the data sets. It can range from a few dozen ter­abytes to mul­ti­ple petabytes.

The abil­ity to store, ag­gre­gate, and com­bine data and then use the re­sults to per­form deep anal­y­sis have be­come even more ac­ces­si­ble. The dis­cus­sion on big data is at a pre­lim­i­nary stage with CIOs and IT man­agers to­day, and the tempo is pick­ing up real fast.

The rea­son for this is that the CIOs are faced with enor­mous amount of im­por­tant data sets and are turn­ing to mine them for in­sights into busi­ness value. Also, most en­ter­prises are con­tem­plat­ing to vir­tu­al­ize and move to the cloud at some point. All this re­quires a pre-de­ter­mined plan of mov­ing large data as­sets, se­cur­ing them, and a plan to drive an­a­lyt­ics.

Ver­ti­cals that have been tra­di­tion­ally heavy con­sumer-cen­tric and IT-savvy such as re­tail, BFSI and oth­ers such as oil F gas and health­care, which process sig­nif­i­cant amounts of in­for­ma­tion, are turn­ing to ap­ply ex­ist­ing data for busi­ness in­sight.

In­crease in De­mand

An­other fac­tor that will fuel the need for big data is the ever-in­creas­ing growth of dig­i­tal data. A re­cent IMC-EMC study de­ter­mined that In­dia gen­er­ated nearly 40,000 petabytes of data in 2010. It es­ti­mated that In­dia’s share of dig­i­tal in­for­ma­tion will grow 60 times by 2020, driven by the roll­out of 3GIBPA net­works, dig­i­ti­za­tion of tele­vi­sion net­works, and in­creased tech­nol­ogy adop­tion among in­di­vid­u­als, SMBs, en­ter­prises and in gov­ern­ment ser­vices like the unique IM project, cen­sus, among oth­ers.

Big data anal­y­sis can help re­tail en­ter­prises, as it can im­prove the speed and scal­a­bil­ity of a mas­sively par­al­lel data ware­house in cost-ef­fec­tive meth­ods.

Many gov­ern­ment func­tions al­ready have a rec­og­niz­able ‘cloud plus big data’ func­tion, with more com­ing along all the time. An­other ex­cit­ing prospect is the Na­tional In­tel­li­gence Grid (Nat­grid)—imag­ine when it be­comes op­er­a­tional in In­dia, it will in­te­grate the ex­ist­ing 21 data­bases with cen­tral and state gov­ern­ment agen­cies and other or­ga­ni­za­tions in the pub­lic and pri­vate sec­tor such as banks, in­surance com­pa­nies, stock ex­changes, air­lines, rail­ways, tele­com ser­vice providers, chem­i­cal ven­dors, etc.

Health­care de­liv­ery has enor­mous po­ten­tial to move to­wards har­ness­ing enor­mous amounts of pa­tient records and pro­vid­ing ev­i­dence-driven rec­om­men­da­tions that not only change rec­om­mended pro­to­cols but shape over­all health­care pol­icy. Be­fore long, health­care will un­doubt­edly be a ‘cloud plus big data’ in­dus­try.

Cloud Com­put­ing

The most im­por­tant driver for big data is cloud com­put­ing. In one sense, the move to cloud (whether pri­vate, pub­lic, or hy­brid) sets the stage for big data. Var­i­ous in­dus­try ex­perts sug­gest that the time now is about cloud meet­ing big data. Cloud com­put­ing makes big data pos­si­ble by pro­vid­ing an elas­tic pool of re­sources to han­dle the mas­sive scale of big data. Through cloud com­put­ing, IT re­sources are more ef­fi­cient and IT teams are more pro­duc­tive, free­ing up re­sources to in­vest in big data.

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