Insights for a successful Big Data Strategy

Although Big Data is all around us, the reality is that only a small fraction of CIOs are successfully tackling it head-on. Our experiences working with large organizations on Big Data projects suggest that there is frustration in organizations trying to decide what the best course of action is in this brave new world. There is a lack of vision and a fear of making mistakes.

But don't worry...with a few fundamental rules governing your Big Data plan, you will be on your way to successfully realizing your goals.

There are six ways to improving your Big Data strategy right now:

1. Invest in the right skills before technology

More important than technology is having the right skills, of which three are distinctly required:

• The ability to frame and ask the right business questions, with a clear line of sight as to how the insights will be used
• Use disparate open source software to integrate and analyze structured and unstructured data
• Bring the right statistical tools to bear on the data to perform predictive analytics and generate forward-looking insights

2. Experiment with focused Big Data pilots

Start by identifying the most critical business issues and how Big Data may contribute to finding solutions. Bring various sources of data into a Big Data Lab where these pilots can be run before major investments in technology are made.

3. Find the needle in the unstructured hay

Semi-structured and unstructured data is top of mind among organizations. It's important to ensure you have the appropriate technology to store and analyze unstructured data. Also, prioritize and focus on the unstructured data that can be linked back to an individual and prioritize the unstructured data that is rich in sentiment and informational value. Most importantly do not just analyze unstructured data, use it.

4. Data poor, insight rich is much better than data rich, insight poor

The risk of data and analysis overload without commensurate actionable insight is at its peak. Many organizations have never acted upon the information they already have, even before the world of Big Data. Generating meaningful insights and acting on them should be the first order of business.

5. Think operational analytic engines, not just analytics

Businesses need to shift their mindset from doing traditional offline analytics to building technology-powered analytic engines that enable near-time or real-time decision making. We recommend that companies take a measured test and learn approach.

6. Adapt organizational processes to take advantage of Big Data

The Big Data world enables one to act in near- or real-time. However, many organizational processes are not prepared for this shift. Taking advantage of Big Data is not just about people and technology, but also the processes behind data collection, insight generation, business decision making, and insight application.