Based on the survey more than 90 respondents agree that with Big Data they can

Based on the survey more than 90 respondents agree

This preview shows page 19 - 21 out of 46 pages.

Based on the survey, more than 90% respondents agree that with Big Data they can take better-informed business decisions by analyzing more data than they are currently processing. However, only 57% respondents agree that existing Big Data kgdmlagfk [Yf `]dh l`]e lg Y[`a]n] l`] \]kaj]\ ^mf[lagfYd gZb][lan]k J]^]j Õ_mj] 0!& 93% 6% 1% We can make more informed decisions by analyzing more data than we do now >a_mj] 0& :]f]Ôlk g^ :a_ <YlY Respondents were asked if they agree or disagree with the above statements with j]kh][l lg Z]f]Õlk g^ :a_ <YlY Agree < on’t know < isagree 57% 33% 10% We understand business bene Õ ts of : ig < ata tech and solutions Figure 9. Big Data technology awareness Respondents were asked to rate their current awareness level of existing Big Data technology components 19% 20% 16% 12% 15% 15% 18% 15% 65% 63% 56% 65% 65% 63% 51% 57% 16% 17% 27% 23% 21% 23% 31% 27% 0% 20% 40% 60% 80% 100% Non relational databases (e.g: NoSQL) In-memory databases Scale-out architechtures <akljaZml]\ Õd] kqkl]ek =_2 @Y\ggh! Distributed indexing and search =_2 C]q%nYdm] klgj]! Distributed data analytics engines Rule-based stream processing engines Multiple parallel processing systems =pl]fkan] cfgod]\_] Limited knowledge Totally unfamiliar Big Data tech solutions not well understood Low awareness of components related to technology stack limiting Big Data adoption
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Big Data and Enterprise Mobility 20 Recently Big Data has gained prominence in the Indian landscape; however, most organizations in India have limited knowledge of various components that form part of a Big Data technology stack. The current awareness levels are low, since nearly 75% respondents have limited knowledge of the tech components and less than 20% respondents believe they have extensive knowledge and can further drive adoption d]n]dk J]^]j Õ_mj] 1!& Sponsorship is important to drive Big Data adoption During initial stages of adoption, the CIO drives the technology investments related to Big Data solutions. However, as organizations move up the adoption curve, Big Data related initiatives will require sponsorship from business leaders to drive business insights. A single sponsorship model with function heads such as CFO, CMO and others will remain critical for Big Data success. CFOs can use analytics to assess, benchmark and identify gaps across various forms g^ jakc È Zmkaf]kk$ ÕfYf[aYd Yf\ gh]jYlagfYd È ^gj af[j]Ykaf_ klYc]`gd\]j nYdm]& >gj ]pYehd]$ ;>Gk [Yf Ykk]kk l`] aehY[l g^ kmhhda]j jakc gf l`]aj HjgÕl ± Dgkk Y[[gmfl Yf\ e]Ykmj] jakc af l]jek g^ ÕfYf[aYd ljgmZd]k$ YnYadYZadalq Yf\ dYZgj mfj]kl& CMOs can leverage Big Data analytics to determine the effectiveness (the impact on eYjc]laf_ Yf\ kYd]k e]lja[k! Yf\ ]^Õ[a]f[q JGA! g^ nYjagmk eYjc]laf_ ]d]e]flk$ including media, trade promotions and consumer promotions. In addition, insights related to environmental factors such as competitor activity, price changes and category factors could be analyzed using advanced techniques to drive marketing and promotion strategies.
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