Friday, June 6, 2014

Implications of Big Data

By Dean Furst

The new millennium is barely a teenager, but has already developed an identity of its own, Cisco estimates “…by the end of this decade, the number of connected devices will grow from 9 billion today to over 50 billion.”[1] What’s even more staggering is the amount of data that’ll be transmitted, shared, and downloaded between them. Online information will be collected through social media sites, search engines, downloads, uploads, and real time security cameras in cars and buildings. There are algorithms to evaluate how drivers react to incoming traffic, how consumers conduct themselves in department stores, and even ones to predict customer’s next online click before they've made the previous one. All of these algorithms base their documentation off actions made by consumers.

The problem with ‘big data’ is that few corporations have the database management systems to process of sheer size of the information. Usually only governmental entities and organizations with advanced central computer processing power have the ability to make sense of, identify trends, and make conclusions from the data. It’s estimated from a recent IBM study that surveyed 1000 business professionals said that “63% of respondents indicated that the use of information (including big data) and analytics is creating a competitive advantage for their organizations–a 70% increase in the past two years alone.” [2] In the modern marketplace, the abilities stated above are creating a bigger inequality (or advantage, however you wish to view it) between the two sets of organizations, those who have the processing power to understand ‘big data’, and those who lack it.

Seeing as internet traffic will soon pass 100 billion terabytes in a few short years, Silicon Valley startups are banding together under the same banner; providing cost-sensitive way to collect and interpret data. Cloudera, one of these such companies, offers a package called Hadoop, which is basically a software package that is able to accommodate the overwhelming data. The price? $525,000, and that doesn't factor in the annual support costs or the installation fee.  Hadoop’s fees rank as some of the most affordable around. Recall a point earlier about smaller companies having trouble trying to afford the operating systems necessary to make sense of the data traffic. Smaller companies simply can’t stomach that kind of a cost, or don’t see it as a worthy investment in their current standing. The price alone is enough to create an inequality in the market, providing wealthier and more developed firms with the ability to gain a competitive advantage in evaluating the data faster and cheaper.

But data alone means little in the competitive market if you can’t find a way to offer its services to your customers. The majority of organizations that have the ability to fabricate conclusions from the data are able to better understand consumer trends in spending and demands. The companies that aren’t able to number-crunch to the same magnitude often outsource their analysis elsewhere. For example, McKinsey and Company employees thousands of algorithm analysts and tech geniuses to evaluate and pick over terabytes of data, coming up with meaningful conclusions for their clients. However, many organizations lack a comparable human supply of brain power, or rather, it would be too costly to employ the necessary people to have it done. This leads us to an interesting dynamic.  

A dynamic well put by Nielson, a global information company, which stated “…smaller players have historically relied more heavily on something their larger counterparts could only dream of—a personal relationship with their customers. Today, however, big data isn’t just for the big guys.”[3]  

Data is unique to a specific consumer type, and even to each consumer. Companies that can individualize their findings, predict future patterns for spending and investing, and offer strategic planning in real time will soon monopolize the market for client services. Nielson also stated in their recent poll of over 2000 small business owners that “even with new solutions tailored for small business, a large portion of owners still lack the expertise and the time to make good use of the information.”[4] This explains why the current businesses that are best adapted to analyze big data are usually government entities or specialty firms. But as always, companies evolve and adapt, and now that the amount of data transferred between devices nowadays is more than the entire amount of data transferred during the WWII years, it's a necessary evolution to stay competitive in the marketplace. Utilizing this advantage has become a pivotal point for many business owners and CEOs. In a recent survey of professionals, the software company SAS  found that “73 percent of survey respondents say their collection of data has increased ‘somewhat’ or ‘significantly.’”[5] For those organizations stated by the survey as “strategic data managers - those with a well-defined data management strategy that focuses on collecting and analyzing the most valuable data – tend to financially outperform their competition more than others  - 53 percent, compared with 36 percent.”[6]

Some companies adopt the new trend of hiring new analysts and  data managers who specialize in the collection and understanding of data, others purchase the computing power to rival (or get as close to as legally possible) the computers at the NSA or other governmental entities. Business models are changing, evolving, and becoming more complex, and data analytics are the base from which to build on. It’s more advantageous to update your existing data metrics environment to accommodate the influx than try to run modern logistics on an outdated system. Bringing it full circle back to Cloudera, Intel just invested over $700M into the company for further research, but the problem exists where the managers and employees lack the skills necessary to make sense of the data. Intel Vice-President Jason Waxman stated in an article that the Hadoop system “isn’t a magic fix…companies are going to need people who understand what they’re looking for.”[7]

Many small businesses feel threatened by expensive operating systems, terabytes of information, and the unique language that data uses. But contrary to popular belief, smaller companies who are on par with the latest technological advances are able t bo access the services offered by these larger corporations. The key word is ‘services,’ they aren’t spending three quarters of a million dollars on software; they’re simply using pre-existing services to personalize their client relationships. There will be organizations similar to Cloudera and Hadoop that are made available to small businesses, because there exists an obvious market for the services. Smaller companies build their revenue on interpersonal client relationships, and understanding data is an added benefit that could maximize profits.

[1] "Big Data for the Real World." VentureBeat. VentureBeat, 6 Feb. 2014. Web. 04 June 2014.
[2] “New Study Details How Enterprises Use Big Data | The Big Data Hub." New Study Details How Enterprises Use Big Data | The Big Data Hub. IBM Information Management, 17 Oct. 2012. Web. 04 June 2014.
[3] "Newswire ." How Small Businesses Can Scale the Big Data Barrier. Nielson, 18 Mar. 2014. Web. 05 June 2014.
[4] "Newswire ." How Small Businesses Can Scale the Big Data Barrier. Nielson, 18 Mar. 2014. Web. 05 June 2014.
[5] Troester, Mark. "Small Business, Big Data." Business Analytics and Business Intelligence Software. SAS, n.d. Web. 05 June 2014.
[6] Troester, Mark. "Small Business, Big Data." Business Analytics and Business Intelligence Software. SAS, n.d. Web. 05 June 2014.
[7] King, Ian. "Big Data Is Really About Small Things." Bloomberg Business Week. Bloomberg, 4 June 2014. Web. 05 June 2014.

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