IBM Big Data Study

The IBM Institute for Business Value recently completed Big Data research and released a report titled Analytics: The real-world use of Big Data. As the report states, companies have been dealing with large volumes of data for years (think billions of call center records collected by Telecommunication companies). But the report also identifies the two trends that make this era of big data different:

  • The digitization of virtually “everything” now creates new types of large and real-time data across a broad range of industries. Much of this is non-standard data: for example, streaming, geospatial or sensor-generated data that does not fit neatly into traditional, structured, relational warehouses.
  • Today’s advanced analytics technologies and techniques enable organizations to extract insights from data with previously unachievable levels of sophistication, speed and accuracy.

Some key survey findings:

  • 63 percent – nearly two-thirds – of respondents report that the use of information (including big data) and analytics is creating a competitive advantage for their organizations.
  • Respondents whose organizations had implemented big data pilots or deployments were 15 percent more likely to report a significant advantage from information (including big data) and analytics compared to those relying on traditional analytics alone.
  • Only 7 percent of respondents believe that big data means social media data. Fewer than half of respondents with active big data initiatives reported collecting and analyzing social media data; instead, respondents said they use existing internal sources of data in their current big data efforts. I’ve had executive dialog in the past month that is consistent with this finding. Many companies can extract significant value from existing data by leveraging advanced forms of analytics.
  • Across industries, the business case for big data is strongly focused on addressing customer-centric objectives
  • A scalable and extensible information management foundation is a prerequisite for big data advancement
  • Organizations are beginning their pilots and implementations by using existing and newly accessible internal sources of data
  • Advanced analytic capabilities are required, yet often lacking, for organizations to get the most value from big data
  • Organizations engaged in big data activities start with a strong core of analytics capabilities designed to address structured data. They then add capabilities to take advantage of both semi-structured (data that can be converted to standard data forms) and unstructured (data in non-standard forms)
  • More than 75 percent of respondents with active big data efforts reported using core analytics capabilities, such as query and reporting, and data mining to analyze big data, while more than 67 percent report using predictive modeling.
  • 71 percent of active big data efforts rely on data visualization skills
  • Fewer than 25 percent of respondents with active big data efforts reported having the required capabilities to analyze extremely unstructured data like voice and video
  • The report identifies four Big Data adoption stages: Educate, Explore, Engage, Execute

In order to maximize value from big data efforts, the report provides five recommendations:

  • Commit initial efforts to customer-centric outcomes
  • Develop an enterprise-wide big data blueprint
  • Start with existing data to achieve near-term results
  • Build analytics capabilities based on business priorities
  • Create a business case based on measurable outcomes.

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