By Pranav Nagarajan
It’s no secret that the data space has been growing at practically unprecedented levels. Everyone knows it. But why? What has changed in the past decade or so that has brought practices like data integration, curation, storage, virtualization, etc. into the forefront of the high-tech industry?
To illustrate this growing need to leverage the power of data, let’s look into the struggles currently being experienced by the likes of department stores like Macy’s, JCPenney, etc. There was once a time where an on-site sale at a traditional brick-and-mortar store was an adequate measure to reel in customers. However, with a more tech-focused millennial generation, it’s the online sales offered by the variety of online retailers that truly affect corporate revenue streams. These department stores, thus struggle to attract the younger audience, which only grows in proportion with every passing second. These failures, at least in the past few years, have led to hundreds of stores being closed across the nation. Even those few stores lucky enough to escape these mass closings are subject to layoffs. Now...how does any of this tie to data?
As mentioned earlier, part of the issue lies in the inability to attract the younger audience into traditional brick-and-mortar stores. However, if companies were able to leverage their data, which many now have, they would be able to predict some of the more “spontaneous” patterns associated with millennial shopping habits. You could visualize each person having a virtual list with every purchase they have every made within a given store. Extend this model to the entire shopper base of this given store, and you’d have quite the pile of data. However, with a proper analytics tool in place, particularly one that enables predictive analytics, you could delve a little deeper into these individual purchases, and begin to ascertain the larger picture, that being changes in the overall market. Now this tool might not save the already struggling department stores, however, its capabilities would likely improve revenue streams, allowing these brick-and-mortar stores to remain in existence for that much longer. In other words, an analytical platform that enables something like predictive analytics, though somewhat costly in itself, could affect thousands in cost savings, not to forget the thousands of jobs saved.
After adding this invaluable tool to a modern corporation, an equally important measure that must be taken is protecting the masses of incoming data. A single breach, perhaps using Yahoo’s recent scandal as an example, where 500,000,000 users had their user information compromised, could ultimately lead to the demise of a company. Yahoo, however, is a large enough corporation to sustain the damages of such a breach; a smaller company might not be so fortunate. Protecting a company’s data is equivalent to ensuring the safety of a company’s assets, wherever they may be held. Data is just as much a financial asset as is an investment within a corporate portfolio. Every company takes steps to ensure the utmost security on asset management end and it would be foolish to act any differently with the storage of data. This is especially true as more and more data becomes cloud based, where hacks and breaches are marginally more prevalent. Much the way analytical tools are present, security platforms are also available that protect servers from the likes of DDOS attacks, malware injections, etc. With that, data, is a vital tool to the success of any 21st century corporation, and like any asset, sufficient measures to protect its integrity must be taken.
Data is thus a versatile, yet necessary tool that should be be leveraged within any corporation striving for betterment. Though only the basics of analytics and security platforms have been discussed, the industry as a whole is booming, and making use of these innovations in the field are to the benefit of any modern business. Data thus stands as a powerful information tool, one carrying a certain financial purpose much like a currency.
"5 Ways Companies Are Using Big Data to Help Their Customers." VentureBeat. IDA Singapore, 14 Apr. 2014. Web. 18 Mar. 2017.
Yadron, Danny. "Five Simple Steps to Protect Corporate Data." The Wall Street Journal. Dow Jones & Company, 19 Apr. 2015. Web. 18 Mar. 2017.