Sink or Swim? Five Steps to Big Data ROI

In 1997, we saw the first mention of the buzz phrase “big data” in a research paper for the NASA Ames Research Center. Scientists are no longer the only ones discussing the promise of big data; rather it has become nomenclature for the entire technology industry at large.

According to Cisco, by 2021 the annual global IP traffic will reach 3.3 zettabytes per year, skyrocketing past previous years’ data growth. Nearly 20 years after big data made its debut, we are still mulling over what to do with the all-encompassing buzzword.

The industry has seen a significant bump in investments. Just this year alone, $57 billion will be invested to bring the realities of big data to companies and individuals. Whether we consider technologies that allow us to maximize computation, or algorithmic accuracy, analysis or even deeper knowledge, the question remains – how can we leverage big data?

Here are five steps to maximize your big data investment and ensure a positive ROI:

As with any exciting trend, people are jumping quickly on the big data bandwagon. Unfortunately, most organizations invest in big data without first identifying their actual business needs.

To be successful, organizations must sit down and determine a problem and goals before pursuing a big data initiative. It sounds obvious, yet as the concept of big data grows, so too do the problems. Determining the underlying issue will catapult any organization down the right road to a solution and success.

Much of the technology available to manage the ever-swelling pool of data is free or open source. And just like most free things in life, there is always a catch. Just because the software itself doesn’t require a payment does not make it cheap or easy to install and operate. While the tools themselves may be free, the skills required to implement, configure, debug, manage and develop are hard to find and can be expensive.

Open source big data components tend to lack the breadth and depth of operations and maintenance capabilities that most traditional platforms have had for decades. This puts additional burdens on IT resources to manage and monitor.

Organizations and their customers do not care that it is open-source.  They care that the data is governed and secured.

While free may sound tempting, it’s important to compare the total costs and benefits of open-source versus an enterprise-grade solution. You may find the enterprise solution is the most cost effective and painless way to value in the long run.

The proliferation of big data tools and products are most valuable when they are properly matched, and all have a significant role to play in the modern data ecosystem. However, understanding that they are not a cure-all is critical. Rather, such tools are just parts of a larger and more complex ecosystem that is now becoming the new blueprint for enterprises.