Can In­dia be a hub for Big Data?

In­dia is ex­pected to emerge as the pre­ferred des­ti­na­tion for an­a­lyt­ics and IT ser­vices for Big Data due to its pre-em­i­nence in IT-BPO ser­vices and Big Data tal­ent avail­abil­ity. Let’s take a look at In­dia’s ad­van­tage in the Big Data op­por­tu­nity

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In­dia is ex­pected to emerge as the pre­ferred des­ti­na­tion for an­a­lyt­ics and IT ser­vices for Big Data due to its pre-em­i­nence in IT-BPO ser­vices and Big Data tal­ent avail­abil­ity. Let’s take a look at In­dia’s ad­van­tage in the Big Data op­por­tu­nity

Global Big Data mar­ket op­por­tu­nity is es­ti­mated to touch USD 25 bil­lion by 2015, ac­cord­ing to a joint study by NASS­COM and CRISIL Global Re­search & An­a­lyt­ics. So how is In­dia placed to lever­age the op­por­tu­nity? If you con­sider in­de­pen­dent re­search and re­ports, there is ev­ery rea­son to be­lieve that Big Data presents a gold­mine of op­por­tu­nity to the coun­try.

In­ter­est­ingly, short­age of an­a­lyt­ics tal­ent, which is emerg­ing as a sig­nif­i­cant Big Data chal­lenge glob­ally, is where lies the big­gest op­por­tu­nity for In­dia. Ac­cord­ing to McKin­sey, the U.S. alone faces a short­age of 140,000–190,000 an­a­lysts and 1.5 mil­lion man­agers who can an­a­lyze Big Data. When it comes to skills, with an abun­dance of math­e­mat­ics and statis­tics tal­ent and one of the largest pools of en­gi­neer­ing tal­ent in the world, In­dia is def­i­nitely fa­vor­ably placed. In fact, In­dia is just be­hind the U.S. in terms of tal­ent avail­abil­ity and the in­ten­tion of ser­vice providers to build tal­ent. Con­sider th­ese facts: In­dia churns out more than 2.5 mil­lion univer­sity grad­u­ates and about 7,50,000 post grad­u­ates ev­ery year, of which 7,00,000 stu­dents are grad­u­ates in math­e­mat­ics and science. Fur­ther, more than 60 per­cent of an­a­lyt­i­cal work­force in In­dia has a work ex­pe­ri­ence of 3-10 years.

In ad­di­tion, with In­dia al­ready cater­ing to busi­ness an­a­lyt­ics needs of global multi­na­tion­als at the best pos­si­ble per­for­mance-to- cost ra­tio, the coun­try has a huge po­ten­tial to

sup­ply data sci­en­tists for the Big Data in­dus­try.

This is sup­ple­mented by ef­forts from IT ma­jors, which have been ty­ing up with uni­ver­si­ties in In­dia to in­tro­duce cour­ses in var­i­ous ar­eas of Big Data. For ex­am­ple, IBM has part­nered with 500 uni­ver­si­ties in In­dia to help more than 30,000 stu­dents de­velop skills in pre­dic­tive an­a­lyt­ics.


The trans­for­ma­tional power of Big Data is huge, as en­ter­prises can find unique in­sights from large chunks of data at a faster pace. When en­ter­prises have this ca­pa­bil­ity, they can do bet­ter fore­cast­ing of events, cre­ate bet­ter cus­tom­ized prod­ucts tai­lored to dy­namic cus­tomer pref­er­ences and make bet­ter man­age­ment de­ci­sions.

Con­sul­tancy firm, McKin­sey, for ex­am­ple, es­ti­mates that Big Data will add USD 155 to USD 325 bil­lion to the U.S. econ­omy by 2020, which rep­re­sents 0.8 to 1.7 per­cent of GDP. By 2020, McKin­sey es­ti­mates that the wider adop­tion of Big Data an­a­lyt­ics could in­crease an­nual GDP in re­tail­ing and man­u­fac­tur­ing by up to USD 325 bil­lion, and save up to USD 285 bil­lion in the cost of health­care and govern­ment ser­vices.

Take a sec­tor like health­care where Big Data has al­ready made an im­pact through its abil­ity to spot un­known pat­terns. In the health­care sec­tor,

McKin­sey es­ti­mates that the wider adop­tion of Big Data an­a­lyt­ics could in­crease an­nual GDP in re­tail­ing and man­u­fac­tur­ing by up to USD 325 bil­lion

data is typ­i­cally un­struc­tured and comes from a va­ri­ety of sources such as X-rays, MRI scans and elec­tronic med­i­cal records. If this ocean of data is an­a­lyzed, doc­tors can cor­re­late past trends with de­mo­graphic data and au­to­mat­i­cally iden­tify pat­terns and pa­tients who are more sus­cep­ti­ble to dis­eases.

A case in point is a pro­ject by the Univer­sity of Cal­i­for­nia in San Fran­cisco, which uses smart­phones to study a base of close to 1 mil­lion peo­ple who will use mo­bile health ap­pli­ca­tions to trans­mit data re­lated to their heart rate, pulse rate and blood pres­sure. The aim is to an­a­lyze the huge amount of data col­lected and de­velop ac­cu­rate mod­els to pre­dict the oc­cur­rence of heart dis­ease in peo­ple. Sim­i­larly, the Amer­i­can So­ci­ety of Clin­i­cal On­col­ogy is us­ing Big Data to per­son­al­ize can­cer treat­ment and help doc­tors de­ter­mine the best treat­ment for spe­cific pa­tients.

Big Data is also be­ing used in a va­ri­ety of use cases. The Van­cou­ver Po­lice Depart­ment in Canada is us­ing

Big Data an­a­lyt­ics for mak­ing its re­gion safe by an­a­lyz­ing crime-re­lated data and uses th­ese in­sights to pre­dict more ac­cu­rately where crimes are likely to oc­cur. Ford col­lects data from sen­sors in­stalled in over 4 mil­lion cars, which is used by its engi­neers to un­der­stand how the car per­forms in dif­fer­ent en­vi­ron­ment and road con­di­tions. The an­a­lyzed in­for­ma­tion can be de­liv­ered via a mo­bile app to the driver, and give them in­sights on the key fac­tors that af­fect a ve­hi­cle’s per­for­mance.

Re­tail gi­ant, Wal­mart, uses Big Data an­a­lyt­ics to track so­cial me­dia men­tions on lo­ca­tions, peo­ple or prod­ucts and uses this in­tel­li­gence to bet­ter tai­lor its prod­uct of­fer­ings. Big Data can also be used for pre­dict­ing re­sults of elec­tions.

Closer home, the UIDAI’s Aad­har pro­ject is a great ex­am­ple of what can pos­si­bly be done us­ing Big Data an­a­lyt­ics. Once the sys­tem is fully de­vel­oped, it can be­come the foun­da­tion for govern­ment func­tions and or­ga­ni­za­tions to an­a­lyze trans­for­ma­tional pos­si­bil­i­ties in ser­vices, such as free ed­u­ca­tion, pub­lic dis­tri­bu­tion sys­tems and pen­sion schemes us­ing what-if sce­nar­ios.

Com­pa­nies are also us­ing Big Data an­a­lyt­ics to im­prove pro­cesses and in­crease ef­fi­ciency. For ex­am­ple, Cen­tral Bank of In­dia is us­ing IBM Big Data an­a­lyt­ics to cut plan­ning cy­cle time in half, in ad­di­tion to gain­ing the ca­pa­bil­ity to track de­posits, loans and non-per­form­ing loans data on a daily ba­sis. As a re­sult of IBM’s so­lu­tion for cor­po­rate per­for­mance man­age­ment, the com­pany is now able to gain bet­ter in­sights into branch and re­gional of­fice per­for­mance, al­low­ing for fur­ther flex­i­bil­ity and quicker shifts in strat­egy to drive im­proved re­sults while also main­tain­ing reg­u­la­tory com­pli­ance.

Sim­i­larly, Go­drej Con­sumer Prod­ucts Ltd. (GCPL), a ma­jor player in the In­dian FMCG mar­ket is us­ing IBM Big Data an­a­lyt­ics to re­spond to cus­tomers’ de­mand and drive mar­ket ex­pan­sion. This has helped GCPL to drive ef­fi­ciency, gain bet­ter vis­i­bil­ity, im­prove con­trols and per­for­mance across ge­ogra­phies. As a re­sult, GCPL is able to make right de­ci­sions on stock place­ment thus pro­vid­ing its cus­tomers with greater prod­uct va­ri­ety at a lower cost, al­low­ing the com­pany to main­tain an edge over the mar­ket com­pe­ti­tion.

Apart from en­abling com­pa­nies to cater to in­di­vid­ual needs of their cus­tomers, Big Data an­a­lyt­ics also has the po­ten­tial to solve real world prob­lems. For ex­am­ple, could the im­pact of the re­cent catas­tro­phe and dev­as­ta­tion caused by the floods in Ut­tarak­hand could have been pre­vented or marginally re­duced us­ing Big Data? A pos­si­ble so­lu­tion can be seen from an ini­tia­tive called Dig­i­tal Delta launched by IBM in the Nether­lands. This pro­ject ag­gre­gates and an­a­lyzes in­for­ma­tion from mul­ti­ple and di­verse sources to pro­vide au­thor­i­ties with in­sights to bet­ter man­age sit­u­a­tions dur­ing ex­treme weather con­di­tions. By mod­el­ing weather events, the govern­ment can de­ter­mine the best course of ac­tion (such as di­vert­ing wa­ter from low ly­ing ar­eas) us­ing a real-time in­tel­li­gent dash­board.


In­dia is also see­ing the emer­gence of a huge num­ber of spe­cial­ized star­tups to tap the op­por­tu­ni­ties in the Big Data do­main. Most of the star­tups in the

space are pri­vate and char­ac­ter­ized by a small base of young em­ploy­ees. A case in point is a Ban­ga­lore-based firm Bi­zosys, which cur­rently has nine team mem­bers. At the core of the com­pany’s Big Data of­fer­ings is its open source search and an­a­lyt­ics engine, HSearch, which pro­vides real-time per­for­mance on Apache Hadoop plat­form. “Most unique as­pect of HSearch is its abil­ity to deal with struc­tured and un­struc­tured data to­gether. Our so­lu­tion in­cludes crawlers and col­lec­tors for data ac­qui­si­tion and in­ges­tion, data cleans­ing and trans­for­ma­tion to dis­cover en­ti­ties and their struc­ture to ren­der data more us­able,” says Su­nil Gut­tula, CEO and Co-founder, Bi­zosys.

The three-year-old startup al­ready has sev­eral cus­tomers in its kitty, in­clud­ing Poin­tCross, a cross in­dus­try so­lu­tion provider to Biopharma R&D com­pa­nies and up­stream oil & gas ex­plo­ration and pro­duc­tion com­pa­nies; a lead­ing For­tune 500 in­vest­ment bank; and a U.S. based tele­com value added ser­vice provider.

La­ten­tView is an­other in­ter­est­ing startup in the Big Data space. The

“Of late, we’ve no­ticed a good amount of In­dian SMBs div­ing into the Big Data pool and we see more In­dian cus­tomers on­board than be­fore”

Prashant Kumar

Founder, Promp­tCloud

firm uses tech­nolo­gies like Hadoop, NoSQL, Par­al­lel R and Hive to pro­vide Big Data-re­lated con­sul­tancy ser­vices, be it for struc­tured or un­struc­tured data. The firm has data sci­en­tists who have sig­nif­i­cant ex­pe­ri­ence us­ing th­ese tech­nolo­gies to solve busi­ness prob­lems. “Over the years, we have seen that cus­tomers need a lot of hand­hold­ing in this space and many times, a stand­alone prod­uct doesn’t suf­fice,” says Venkat Viswanathan, Founder & CEO, La­ten­tView.

Cur­rently, 90 per­cent of La­ten­tView’s busi­ness comes from the U.S., with some of the largest retailers and tech­nol­ogy com­pa­nies be­ing its clients.

Es­tab­lished in 2009, Promp­tCloud is yet an­other startup in the Big Data space that fo­cuses on pro­vid­ing Dataas-a-Ser­vice.One of the com­pany’s prime of­fer­ings is low la­tency largescale crawlers, which de­liver data feeds from ap­prox­i­mately 100,000 sites or more for news, blogs, ar­ti­cles, stock data, etc. Its an­other of­fer­ing pro­vides site spe­cific data crawl and ex­trac­tion where the com­pany crawls the sources of client’s in­ter­est on the web, and for­mats that data into an XML/CSV as per their de­sired schema. Th­ese data feeds then get de­liv­ered via API on an on­go­ing ba­sis as per the client’s de­sired fre­quency.

The com­pany is about to dou­ble its cus­tomer base com­pared to what it had a cou­ple of quar­ters back. The core of Promp­tCloud’s cus­tomer base is in the U.S., U.K., Ger­many, Switzer­land, Hong Kong, Sin­ga­pore and Is­rael. Its client list in­cludes one of the lead­ing play­ers in mar­ket re­search, Con­verseon and Canada-based firm Elisys. “Of late, we’ve no­ticed a good amount of In­dian SMBs div­ing into the Big Data pool and we see more In­dian cus­tomers (as well as leads) on­board than be­fore,” says Prashant Kumar, Founder, Promp­tCloud.

With a vi­sion to make data anal­y­sis ac­ces­si­ble to ev­ery­one, Form­cept is an­other in­ter­est­ing startup in the space. The com­pany has built a Big Data Mid­dle­ware, called MECBOT, which is a uni­fied an­a­lyt­ics plat­form that in­cludes batch pro­cess­ing, in­ter­ac­tive anal­y­sis and stream pro­cess­ing ca­pa­bil­i­ties. MECBOT can an­a­lyze un­struc­tured data in the form of doc­u­ments — be it PDF, HTML, Doc, text, tweets — and also struc­tured data stored in re­la­tional data­bases. It al­lows en­ter­prises to write cus­tom­ized ap­pli­ca­tions, called In­tents, on top of the plat­form ac­cord­ing to their busi­ness needs or for tar­get­ing their

end cus­tomers.

Form­cept has re­ceived fund­ing from Cen­tre for In­no­va­tion, In­cu­ba­tion and En­trepreneur­ship (IIM Ahmed­abad ini­tia­tive) and has also re­ceived govern­ment grant.

Form­cept has part­nered with a few key sys­tem in­te­gra­tors who can take its prod­uct to their cus­tomers in var­i­ous do­mains and build ap­pli­ca­tions on top of it. It has also part­nered with ser­vice providers in the data an­a­lyt­ics space who can pro­vide a com­plete so­lu­tion to their cus­tomers across do­mains. In ad­di­tion, Form­cept has part­nered with a few suc­cess­ful star­tups who have a good cus­tomer base.

Started by ex-IBMers, S Anand, Naveeen Gattu and J Ra­machan­dran, Gramener fo­cuses on data con­sump­tion so­lu­tions, ir­re­spec­tive of the size of the data so that busi­nesses get en­abled. Con­trary to the in­dus­try no­tion of Big Data be­ing the large­ness of the data sets, Gramener de­fines “big-ness” of the data as any size of data, which can­not be used ef­fec­tively to make rapid busi­ness de­ci­sions.

While there are many com­pa­nies

“In­dia, pri­mar­ily thought to be a skill-source des­ti­na­tion, is rapidly chang­ing into a tar­get mar­ket for busi­nesses” J Ra­machan­dran CEO, Gramener

— both startup and tech­nol­ogy gi­ants — data con­sump­tion so­lu­tions from Gramener have found their own niche in the Big Data/an­a­lyt­ics ecosys­tem.

“We are able to co- ex­ist with th­ese com­pa­nies and in fact, sym­bi­ot­i­cally help their so­lu­tions to be con­sumed bet­ter by their cus­tomers. For ex­am­ple, we are help­ing a tele­com cus­tomer con­sume Big Data pro­duced by a tech­nol­ogy gi­ant who is the tele­com gi­ant’s IT part­ner,” states J Ra­machan­dran, CEO, Gramener.

The com­pany has cre­ated a tech­nol­ogy plat­form (patent pend­ing), which reads het­ero­ge­neous data sources in prac­ti­cally all data for­mats — both struc­tured and un­struc­tured — and pre­pares the data in a man­ner so that the com­pany’s visu­al­iza­tion servers can con­sume the data and cre­ate quick out­puts based on data anal­y­sis. This anal­y­sis is pre­sented to the cus­tomers in an easy to un­der­stand vis­ual for­mat, which can be drilled down for spe­cific in­sights.

Gramener cur­rently finds the North Amer­i­can mar­ket well poised to ab­sorb data con­sump­tion so­lu­tions as data gen­er­a­tion and avail­abil­ity have ma­tured in th­ese ge­ogra­phies and hence the need for co­her­ent con­sump­tion has be­come more per­ti­nent. The com­pany also finds the op­por­tu­nity in In­dia very ex­cit­ing and plans to ac­quire more In­dian cus­tomers.

“In­dia, pri­mar­ily thought to be a skill-source des­ti­na­tion, is rapidly chang­ing into a tar­get mar­ket for busi­nesses due to growth econ­omy, pur­chas­ing power of con­sumers and mas­sive in­fra­struc­ture spend. To serve and grow in this mar­ket place, busi­nesses need tools of to­day — Big Data and an­a­lyt­ics,” opines Ra­machan­dran.


Ac­cord­ing to the in­dus­try ex­perts, In­dia cur­rently has a unique ad­van­tage in the Big Data space. How­ever, a lot of work needs to be done if it has to fully re­al­ize its po­ten­tial in terms of a re­fined tal­ent pool, hav­ing a ma­ture ser­vice provider land­scape and in­no­va­tive ser­vice de­liv­ery.

Al­though, In­dia cur­rently con­trib­utes to just about 2.5 per­cent of the global Big Data mar­ket, this num­ber is grow­ing rapidly. The in­sa­tiable ap­petite for data gen­er­a­tion among the mil­len­nial pop­u­la­tion will only has­ten this growth. Given the sheer size of the data-gen­er­at­ing young pop­u­la­tion, it’s only a mat­ter of time that In­dia will be lead­ing the Big Data race.

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