The concept of big data, when it was first introduced, was pretty scary for enterprises.
Not only was the volume of data doubling every year or two, but the variety of data and the velocity at which enterprises needed to analyze their data was growing too. Today, big data has gone from concept to reality, but there’s still a fear factor associated with big data projects.
Some enterprises, for example, fear that big data tools will be difficult to implement and manage because they’re completely different from their traditional analytic tool sets. Other enterprises are worried that the supply of big data scientists relative to demand will put them at a disadvantage as they look to recruit and retain data analysts.
And most enterprises recognize that more data means more potential to have data dispersed in a disorganized fashion across various departments and applications—making it more difficult to aggregate and analyze their data in a meaningful way.
While it’s true that big data projects are daunting, the potential rewards of big data are simply too big to ignore:
- For healthcare companies, big data is improving medical treatments, driving down costs, and providing better preventive care;
- For manufacturing companies, big data allows them to optimize machine designs, reduce repair costs, and build their products more efficiently;
- For retail companies, big data leads to more customer loyalty, higher sales, and fresher groceries;
- For financial companies, big data means better investment strategies, more accurate market predictions, and improved customer acquisition efforts.
Almost any organization that collects and analyzes large amounts of data to drive business decisions can benefit from a big data solution. But before they do that, they should first benefit from the experience of those who have gone before them. Without the right guidance and expertise, big data projects can (and do) fail.
Some of the things that enterprises need to factor into their big data strategy include:
- Data aggregation — How do we bring all of this data together and avoid the siloed data disasters of the past?
- Data migration — i.e., How will we move all of this data into a place where we can analyze it?
- Data archiving — Where will we put all of this data so we can access it again later?
- Data architecture — Do we need to rethink how we handle, access, and analyze data to accommodate big data’s demands?
- Cloud data — How do we treat data that resides in a public cloud?
Rolta AdvizeX can help you find the answers to those questions (and more) through our Data Advizer engagement. We bring the right people together from your team and from our team to identify the goals, the hurdles, and the measures for success. Then we put together a plan that ensures your big data efforts are aligned around those areas that have the most ROI and deliver the clearest competitive advantage.
After all, it’s not enough to be a data-driven enterprise; you need to know where you’re going and that you’re taking the shortest, safest path to get there. ▪