Big Data: Moving Beyond the Tipping Point?

by CXOtoday News Desk    Aug 16, 2013

big data success

Not long ago, mention of ‘Big Data’ evoked a mixed response. Proponents swore by it while opponents swore at it. Some believed it to be critical to business success while others called it mere hype. Twelve years after researchers first defined data growth challenges and opportunities, analysts now suggest that the global mid-market attitude towards Big Data from ‘over-hype’ to ‘must-have’ technology.

A report published by research firm Techaisle suggests that global SMB spend on Big Data would reach USD 3.6 billion by 2016 from a mere USD 867 million in 2012. The survey indicates that 43% of the mid-market businesses are either actively investing in (18%) or currently investigating  (25%) Big Data.

CXO Today presents some extracts from the report on ‘Global Mid-Market Big Data Adoption & Trends’. Read on…

There is a sizeable opportunity for companies providing Big Data solutions in the SMB segment. Considering that the segment is relatively new, it requires a certain level of IT sophistication and a history in the linear investment in Information Technology enablers to be successful. While these factors predispose larger accounts to Big Data, the competitive imperative to understand customers, innovate products and improve operational efficiencies has already started to reach down to the mid-market, forcing a search for how to leverage primary and secondary data that is generated by the business. 


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Some salient points of the Survey:

·         Only 11 percent of mid-market businesses consider Big Data to be an over hype suggesting that it has crossed the tipping point faster than similar sentiments for cloud adoption at its introduction. Even among the lower mid-market businesses, 29 percent think that Big Data will be an important part of their business decision-making process.

·         Business Intelligence by itself has provided enough business insights, however, mid-market businesses are now looking for extracting business perspectives to drive superior decisions and ultimately achieve superior results.

·         In addition to understanding customers, mid-market businesses are also considering big data analytics as an important initiative to help them improve operational efficiencies

·         There are many different tactical objectives for deploying big data projects but the top among them are sentiment monitoring, generating new revenue streams&improving predictive analytics. It must also be said that businesses have figured out that there is a lot of publicly available data which could be analyzed to their advantage

·         And businesses are expecting some clear cut benefits from big data analytics such as Increased sales, More Efficient operations, Improved Customer service

·         In terms of analytics skill-set and a vision, the potential of linking structured and unstructured data sources to create new business insights is being considered very useful but at the same time mid-market businesses are not really prepared. In fact one-third of mid-market businesses agree that linking structured and unstructured data would be very useful for big data analytics but over 70 percent agree that they have either none or rudimentary capabilities of analyzing unstructured data. This is where they are turning to external help for guidance.

 Techaisle report: Global Mid-Market Big Data Adoption & Trends

Table of Contents

§  Methodology

§  Executive Summary

§  Mid-Market Big data Adoption Trends

o   Adoption Trends by Regions and Employee Sizes

o   Attitude towards big data

o   Mindset driving big data adoption

o   Top business objectives for big data projects

o   Expected benefits from big data analytics

§  Types of Data & Big Data Platform Trends

o   Types of data

o   Cloud vs. On-premise choice

o   Primary platform

§  Role of Structured and Unstructured Data Linkages

o   Usefulness of linking different types of data

o   Role of Big Data as compared to other Analytics

o   Mid-Market Capabilities in Analyzing Unstructured Data

§  Mid-Market Big Data Implementation Challenges

o   Challenges in Implementing big data projects

§  Mid-Market Big Data Business Initiators

o   Business functions driving big data initiatives

o   Consumers of big data insights

o   Overall Process and Success Rates

§  Market Size and Key Segments