Why Companies Can’t Solely Rely on Big Data

Featured article by Robert Cordray, Independent Technology Author

“Big data” is a blanket phrase for data sets too large and complex for traditional processing. Business process management means not just data capture, but mining petabytes of related information for analysis. This means the resource drain of searching, sharing, storing, transferring, and protecting all that data. If you shrink from investing in big data, or diving into data mining and predictive analysis, you may find a few existing shortcuts work fine in fulfilling business needs. There are advantages to big data, but there is common sense.

Creating smarter organizations

A well-planned data and analytics strategy means a wealth of useful information that makes planning smarter and more efficient. Big data is paying off for most common industries, from law enforcement to health care. However, if you don’t really need it, don’t bother. Instead of a company-wide data pool that will have everyone diving in – and possibly drowning – why not ask each department manager exactly what they need? There may be other approaches to accomplish the same goals. There are companies that capture data and crunch numbers so you don’t have to. This is useful information, yes, but decisions should have more practical meaning and clearly defined goals. Hopefully your people already know their business niche. Have them define goals and establish what they need to get there. Stick to data that fulfills a specific business need.

Company-wide communication

It is important for modern organizations to stay on top of a wide customer base, and that means reams of demographic and sales data. It’s also important for teams from different departments or offices taking part in the same initiative to be able to share and work with the same set of data. Big data today means cloud-computing, with the benefits of distributed computing power and near-instantaneous data storage and access from around the globe.

That should not be a starting point, however. Once there is a list of attainable goals, it’s time to strategize. It helps to divide requirements into compartmental segments, or groups with a unique perspective or resources to attain each step. Take a clue from the Agile system of IT development, that can apply to business as a whole. Break down your goals into a series of steps to be achieved. Allot a certain amount of time and resources to attaining, say, 80% of those goals on time. Every department will have its own requisite data set and tools that staff can work with. All that’s needed is a good project coordinator.

Prepared for Growth

You may be collecting an overwhelming glut of information, but one of the advantages of big data is that the infrastructure to support it will also grow. Volumes of data and powerful, adaptable data models are becoming standard. Business analysts can mine useful forecasts from a growing mountain of data. But you don’t have to climb it just because it’s there.

Ask around, and you’d be surprised how many employees are something of a whiz at Excel, which has some great tools for power users, such as charts, pivot tables, and goal-seek scenarios. Don’t overlook simpler database applications like Access. Dedicated and ambitious employees will be only to glad to brush up on their skills. You might even want to have some IT personnel give training classes. These applications can be easily integrated with network sharing, security protocols, and other programs. You’d be surprised how many big data projects are fed by desktop applications that will still be viable, and also more advanced, years from now.

Big data and its infrastructure mean expenditure on hardware, personnel, or outsourcing. Instead of going big data and trying to grow into it, concentrate on getting what you need, as you need it. Be sure you’re getting real benefits from the data capture and analysis you already do, before you take that leap of faith into the principle that more is better.