Data holds power. By now business leaders everywhere understand that big data has the ability to uncover valuable insights and boost efficiency for their company, but many struggle to reap these benefits. Information must first be understood and utilized appropriately, and making the jump from a plan to an executable strategy to definable results is often a bigger journey than initially thought. With a tremendous amount of information overwhelming many businesses today, how do you know if your data is reaching its full potential?
Data cannot be helpful if left hidden or ignored, so it is vital to know what data is entering your organization and from where. After some digging, many are surprised at how many sources of data they didn’t even know were pouring into their company. Dark data, or information that is unused, unstructured, or unknown, is the root of this problem. Consider a modern car that has 30 processors inside of it. Every action that car takes, whether it’s the length of time a turn signal is on, the degrees the steering wheel rotates, or the pressure of the brakes, is data that can be recorded and analyzed for insights. This holds true for your business, regardless of industry. Every process that happens under your roof is likely producing a piece of data that can be reviewed.
Further, consider that a massive 80-90% of all data is unstructured. That means there are troves of raw data entering servers and remaining untouched. Attending to dark data requires looking in the right places, and that begins by asking employees the right questions about the tasks they complete to discern what data is being produced and where it is being housed. A big data talent shortage is making even this initial process a challenge, as it can become difficult for the inexperienced to uncover dark data and the alternative of locating an expert to hire is just as hard.
Recently, a large communications provider approached us with concerns about the visibility of their essential data during a migration. To ensure a smooth process, our team of 12 Data Analysts, three Application Developers, and one Database Administrator considered every potential stream of data and where it would go when migrated. Armed with this knowledge, they chose to install and utilize the right program to keep track of data as it moved, eliminating the chances that any information would go dark. While each case is unique, it often takes a skilled team to shine the light on all of an organization’s data.
When it comes to big data strategy and pain points, discovering and compiling useful information isn’t even half the battle. Accurately analyzing that information takes time and knowhow. Attempting to draw insight from a single piece of data separate from the rest will almost always produce an inaccurate view. Pieces of Information are dependent upon each other to provide context and an answer to the all-important question of “Why?” Without accurate big data analysis, even the best nuggets of raw data cannot be formed into gold.
For example, take this data center migration for a major hospital and health system. It took an expert team of 20 consultants to take on this large-scale project and discover an inaccurate inventory list within the data. Had they not accurately analyzed these pieces of information, then any other data even remotely related to inventory items would be erroneous and therefore misleading. It’s scenarios such as this that made a survey of 1,200 IT executives identify hiring IT talent with analytics skills....
Those that are able to understand what their big data is telling them are already far ahead of the competition. However, the bridge between knowledge and action is a long and precarious one. If data points to a problem or gives an indication that an area can be more efficiently served, then these are opportunities that can only be realized once action is taken. Unfortunately, many organizations that make it this far stumble with the finish line in sight. Whether it is due to employees that are resistant to change, concerns over cost, or a lack of resources, there are more difficulties than solutions at this stage of the game.
A U.S. subsidiary of a $25 billion international banking and financial services institution recently faced a similar dataset dilemma. They understood that their enormous amount of data could meet the needs they required of it, but only if they could fully utilize it. Most importantly, they realized they could not successfully forge ahead on their own. Instead of attempting to implement new software with complex requirements themselves, they found partnering with experts in big data to be a cost-effective and fruitful solution.
There is no clear highway overpass sign that will alert you when your big data reaches its full potential. The goal is not to reach an arbitrary data benchmark, but rather to learn what information flows into your organization, what it means, and how to use it to your advantage. Doing so requires avoiding big data mistakes and the knowledge that only proven big data experience can bring.