It is time to end small thinking about big data. Instead of thinking about how to apply the insights of big data to business problems, we often hear more tactical questions, such as how to store large amounts of data or analyze it in new ways. This thinking is small because it focuses on technology and new forms of data in an isolated and abstract way.
- Big data is really just “data.” What’s the best way to handle all our data?
- Big data is one piece of a larger puzzle. How can we effectively combine it with existing analytics to yield the greatest impact?
- Big data needs to enhance business operations. How can we use big data to create better products and services?
Big data doesn’t mean that we must hit the reset button. We still need to harvest information from enterprise applications and construct a comprehensive structured model of our business. We need to securely manage information as an asset. We need to control access to data to protect privacy and comply with regulations. And we need to enable everyone to explore as much data as possible. Big data doesn’t mean we flip the off switch on all past business intelligence (BI) activities. It means that we understand how to
We must remember that big data isn’t about technology; it is a movement, a mind-set, that’s ingrained in an organization. How can we channel the energy that surrounds big data into a cultural transformation? Movements don’t succeed without a compelling vision of the future. The goal should be to create a data culture, to build on what we’ve done in the past, to get everyone involved with data, and to derive more value and analytics from all the data to make business decisions. This is the real victory to do a better job with everything we have by adding new capabilities
Starting a big data movement involves challenges:
- Transforming company culture to be data-driven and compete on analytics
- Discovering nuggets of information about customers, products, and performance across systems and data formats (ERP, legacy systems, web logs, email, voice, text, social media, and more)
- Making data and analytics accessible to as many people as possible
The right vision for each company will differ, but for most companies a movement should be characterized by:
- Using business questions, not technology capabilities, to drive the architecture
- Increasing self-service access to data to encourage data-driven decisions
- Enabling fast, iterative discovery that allows analytical teams to “swim” in the data and see what signals or trends emerge