Avoiding Big Data Sand Traps

Data management history has shown, it is not what you buy; it is how you are able to use it that makes a difference. According to survey results from the Q4 2012 Forrsights BI/Big Data Survey, this is a story that is again ringing true as big data changes the data management landscape. 

Overall . . .

  • Big technology adoption across various capabilities ranges from 8% to just over 25%.
  • Plans to implement big data technology across various capabilities is as high as 31%.
  • Pilot projects are the preferred method to get started.

However . . .

  • High-performing organizations (15%-plus annual growth) are expanding big data investments by one to two times in many big data areas compared with other organizations.

The key takeaway . . . 

  • For most organizations, big data projects aren't leaving the pilot stage and aren't failing to attain strong return on investment (ROI).

This is not too unlike my golf game. As spring is upon us and the golf clubs are rattling in the closets demanding to be released, I can’t help but think of my horrendous golfing ability and my seeming love affair with sand. I invested in lots of good clubs (tech). I have lots of options (landscape). Yet, I am still forever tossing my golf ball onto the green to escape the sand trap.

This is like many organizations' big data pilots. They enter with enthusiasm and great tools. Sandboxes are created to learn and identify how to get more out of their data. They get stuck and value languishes – sandboxes have turned into sand traps.

Many factors contribute success with big data, specifically: attitude, culture, discipline. However, in terms of technology, patterns are emerging in the way successful organizations combine traditional and emerging data management capabilities. There are also paths to data management landscapes of maturity that organizations can take. 

At the Spring Business Technology Forum on May 6-7 in Washington, DC, I’ll be sharing my findings on today’s data management technology landscape and how to put it into context for your business and data strategy. Here is a preview of what it takes to succeed:

  • Attitude, courage, and discipline. Transforming data into a strategic tool that drives business outcomes is not art, it is science. Success with your data investments means managing data like a business and not just an artifact of the organization.
  • Collector, investor, and innovator. Your data archetype is your data technology road map. Where you are on the path to leveraging data determines which big data technology will benefit you the most. Skip a step and risk the sand trap.
  • Hub-and-spoke architecture. Flexible data management starts with business patterns and linked to big data patterns. There are logical recipes to manage and embrace federated data sources, data types, and information needs. 

Ultimately, understanding the big data landscape isn’t just about what tools are available and what they do. It is about the system created to deliver value and transform the business.

See you there!

Comments

Key Takeaway Confusion

Did you mean to say "For most organizations, big data projects aren't leaving the pilot stage and aren't failing to attain strong return on investment (ROI)?" Or did you intend to say they ARE failing to attain strong ROI?

Just want to make sure I understand the takeaway. Are pilots are long but successful or are they long and worthless?

Thank you for this

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