Most businesses are still in the experimental stage with big data. They are testing out platforms like Hadoop and analyzing how big data can fit into their overall business strategy. Of course, the main reason these businesses have adopted big data in the first place is to derive valuable business insights from them. Unfortunately, many have found this difficult. To address this issue, here are five steps to starting to get real value from big data.
1. Make Analysis a Priority
With all of the hype over the term “big” in big data, it seems some businesses have gotten into the business of collecting and storing massive amounts of data but are not actually deriving any value from it. In fact, a survey of IT and business leaders found that 32 percent of companies invest more than $1 million in gathering and storing data but only 26 percent of those organizations have invested $1million in the analysis of the data they spent millions to collect. It seems, then, that the first step to starting to get better insights is to make analysis the priority. This may require a change in how the IT team works with other departments and a change in culture from the C suite down.
2. Remove the Pressure to Prove a Tactic Right
In the past, data was often used to justify an action that was already taken. A department head going into a budget meeting or a performance review will naturally take any data that supports their work as proof that they are worthy of the funds and resources allocated to them. While there is some value in this form of analysis, if analysis is only used to justify what is already being done, companies might as well stick with their traditional data sets. However, if managers were willing to use the analysis to make changes to the status quo and admit that there are areas to be improved, the analysis will start to have real value for that company.
3. Employ the Appropriate Tools
Many of the issues addressed above can be solved by using the appropriate tools. Hadoop on its own is not particularly enterprise friendly, but many vendors have created their own platforms on top of Hadoop that reduce the need to employ a data scientist. In addition, some cloud computing vendors specialize in big data as a service. These vendors create a database and analysis tools that are enterprise ready, so no time has to be spent on the creation process and more resources can go toward analysis.
4. Visualization
Let’s talk about actually understanding what the data is telling you. While your sales or marketing team may be used to sifting through numbers on their weekly reports, using big data means the amount of numbers is going to be impossible for one person to sift through in a reasonable amount of time. Visualization not only speeds up this sifting process, but also helps put the data into context and identify the key business questions. Harvard Business Review had an excellent example of how visualization demonstrated that only one article of three that went viral on Twitter actually led to click-through and greater traffic on the website even though one of the ineffective articles had data indicating that same correlation.
5. Act on the Insights
In what seems an obvious final step, strategically apply the insights you have gleaned from the analysis. This goes back to the cultural shift mentioned in step two. Managers or executives who are resistant to changing their methods or who simply don’t believe the data because it goes against their instincts may be one of the biggest inhibitors from getting the value from your big data investment. However, the managers who are willing to try applying the insights to their work will start to reap the rewards of what big data can offer them.
It seems that the next big change to the business world may not be big data after all but a shift in business culture spurred by the possibility of big insights. Those businesses that are able to make this leap successfully to an analytical culture will have a huge advantage over those who don’t in the future.
Author Bio: Gil Allouche is the Vice President of Marketing at Qubole. Gil began his marketing career as a product strategist at SAP while earning his MBA at Babson College and is a former software engineer. 
