The Five Markers on Your Big Data Journey

Categories: General

As an enterprise software company, we spend a good amount of time talking about… well… software. But becoming a data-driven company requires far more than great technology. It requires organizations to implement best practices around people and processes. In this blog series, we’re going to cover the five things that our customers do that make the difference between big data success and stagnation. These practices were logged over nearly a decade of work with more than a thousand enterprise customers.

The Journey Requires Organizational Change

Gartner research director Lisa Kart says, “[A] successful advanced analytics strategy is about more than simply acquiring the right tools. It’s also important to change mindsets and culture, and to be creative in search of success.” Without embracing this paradigm shift, Gartner predicts uninspired change:

  • Through 2017, 60% of big data projects will fail to go beyond piloting and experimentation and will be abandoned.
  • Through 2017, fewer than half of lagging organizations will have made cultural or business model adjustments sufficient to benefit from big data.
  • Through 2018, 90% of deployed data lakes will be useless as they are overwhelmed with information assets captured for uncertain use cases.
  • By 2018, 50% of business ethics violations will occur through improper use of big data analytics.

These statistics from Gartner underscore a larger problem. Namely that many enterprises buy into big data while paying very little attention to their people and processes. Below are the five things our most successful customers do on their data-driven journey:

  1. Build a Big Data culture. Executive sponsor(s) lead to encourage and enable fast-paced change.
  2. Assemble the right team. Tightly aligned teams with a mix of industry experts and creative innovators promote success.
  3. Adopt an agile approach for data engineering, data science, analysis. Successful projects start small, fail often and embrace an “iterate to success” approach.
  4. Efficiently operationalize insights. Analytics generate reports, and Big Data generates actions. Successful businesses span organizational gaps by building a bridge between Development and Operations (DevOps).
  5. Govern the data. Successful operations govern at the level of the data.

Throughout this series, we’ll break down each of the above success factors, providing practical tips your organization can implement today. Stay tuned for Building a Big Data Culture coming up next week.

And for a deeper dive on this subject, please register for Cloudera Now. In the general session, Tom Davenport, a noted author and professor on data and analytics, and I discuss what companies get right and where they tend to slip up along their respective data journeys.

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