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Lyndsay Wise

Hi and welcome to my blog! I look forward to bringing you weekly posts about what is happening in the world of BI, CDI and marketing performance management.

About the author >

Lyndsay is the President and Founder of WiseAnalytics, an independent analyst firm specializing in business intelligence, master data management and unstructured data. For more than seven years, she has assisted clients in business systems analysis, software selection and implementation of enterprise applications. Lyndsay conducts regular research studies, consults, writes articles and speaks about improving the value of business intelligence within organizations. She can be reached at lwise@wiseanalytics.com.

Editor's Note: More articles and resources are available in Lyndsay's BeyeNETWORK Expert Channel. Be sure to visit today!

The term “big data” is a bit of a misnomer. Many mid-market organizations feel that big data doesn’t apply to them based on the size and infrastructure assumptions associated with these projects. Consequently, many organizations overlook the benefits of looking at big data as a BI and data management strategy. Whether or not big data should be addressed depends on many factors. Some of these include:

  • types of data being analyzed – this means looking at whether data should/can be stored within a relational database or should be stored separately within another format
  • purpose of analytics – traditional BI environments enable certain types of analytics well, but generally don’t support operational analytics, or the ability to store and access the data variety or complexities associated with big data
  • reason for information storage – big data is broader than BI or analytics and the different applications should be explored
  • level of complexity – sometimes organizations do not have high data volumes, but do have complexities based on industry or company specific requirements that are best handled within a big data infrastructure

These represent a subset of reasons why mid-sized businesses should be looking at whether big data applies within their organizations and what needs to happen to implement a big data framework.

As with all technology projects, more considerations are required than just looking at whether the organization faces challenges that reflect the factors above or others conducive to big data environments. Organizations need to understand their current infrastructure, what they can support, what hardware or cloud based provisions need to be considered, costs of initiating a new data management project, and how all of this will directly affect business. Understanding the bigger picture and where a big data solution might fit within a broader information architecture and how it benefits the company as a whole is one of the first steps of deciding whether it’s the right step for the organization.

Overall, the important thing to remember is not to discredit the potential big data can bring to the organization because it may seem out of reach as open source technologies, internal resources, and general education can help mid-market companies move towards their big data goals. 

This post was written as part of the IBM for Midsize Business program, which provides midsize businesses with the tools, expertise and solutions they need to become engines of a smarter planet. I’ve been compensated to contribute to this program, but the opinions expressed in this post are my own and don’t necessarily represent IBM’s positions, strategies or opinions.

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Posted March 18, 2014 6:31 PM
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