Data analysis – Big Data

The concept of big data has been around for years; most organizations now understand that if they capture all the data that streams into their businesses, they can apply analytics and get significant value from it. But even in the 1950s, decades before anyone uttered the term “big data,” businesses were using basic analytics (essentially numbers in a spreadsheet that were manually examined) to uncover insights and trends.

The new benefits that big data analytics brings to the table, however, are speed and efficiency. Whereas a few years ago a business would have gathered information, run analytics and unearthed information that could be used for future decisions, today that business can identify insights for immediate decisions. The ability to work faster – and stay agile – gives organizations a competitive edge they didn’t have before.

Traditional relational databases cannot deal effectively with Big Data, making it necessary to search for alternatives. New processes and tools may be required to manage the Big Data flowing back and forth across the enterprise, and to process and analyze it.

New storage systems may be needed as well. Data must be collected and stored whether its value is immediately known or not.

A business person submitting a written request to IT no longer makes sense when the need for real time analysis of data in motion is factored in. So, new tools must be acquired or developed in-house for end users to get at the information they need on their own.

Managers may need to add staff or train the current staff to bring the department up to speed on the hardware and software needed to handle Big Data.