What Is Big Data And Why Is It Being Used?

What is Big Data and why is it being used?

Big Data can be defined as “large volumes of data – both structured and unstructured – that inundates a business on a day-to-day basis.” Many companies, both large and small, are currently compiling this marketing, sales, customer, social, and transactional data in hopes of improving decision making across their organizations.

Wired Magazine's Arvind Singh likens Big Data to the new “Black Gold” which, when properly mined and refined, promises to aid businesses in making “sound decisions anywhere and anytime — at the pace required by today’s competitive business landscape”. Singh believes Big Data represents “a tremendous opportunity to drill down and tap into these critical insights.”

What are the benefits of Big Data?

Big Data can help businesses by: 1.) identifying more efficient ways of doing business, 2.) improving product development by catering to the specific needs of customers, 3.) more accurately identifying market trends, and 4.) monitoring and improving their online presence. In short, organizations can utilize Big Data to optimize business processes and ultimately capture market share from competitors.

Many of the largest corporations in the world today are at the forefront of the Big Data revolution. Some key examples include Amazon, purportedly the world’s largest internet company by revenue, which mines it's enormous customer data bank in order to design advertising algorithms and improve customer relations. American Express uses Big Data to analyze and predict consumer behavior. Netflix uses Big Data to select content based on customer viewing habits.

What are the risks of Big Data?

On one hand, businesses that fail to fully embrace Big Data may find that they cease to maintain their competitive advantages in the future. Indeed, experts have warned that some industries may be won or lost based on executives’ abilities to capitalize on this data. Studies conducted by Susan Athey, economics professor at Stanford University, suggest that “when companies inject data and analytics deep into their operations, they can boost productivity and profit that is 5% to 6% higher than the competition.”

On the other hand, if not executed properly, Big Data campaigns may do more harm than good. The challenge is both an organizational and technological one. Research conducted by Mckinsey & Company found that despite the success stories at high-tech companies such as Amazon and Google, legacy companies have not been as successful at capturing the benefits of Big Data. For example, they found that companies may make the initial investment necessary to achieve marginal results yet lack the managerial will necessary to make larger investments, resulting in wasted resources. Mckinsey says that a successful data analytics campaign demands the creation of new senior-management capacity to really focus on data […] managers need to change their way of making decisions to take advantage of analytics.”

Companies must also know how to most efficiently collect, store, and analyze their data. Software Database giant and industry leader Oracle has stated that “how an organization defines its data strategy and approach—including its choice of big data and cloud technologies-- will make a critical difference in its ability to compete in the future”. Oracle defines big data by the four “Vs”:

1.) Volume or amount of data, including low-density, unstructured data such as data feeds, click streams on a web page, mobile app, and network traffic, stored using a hadoop cluster.

2.) Velocity or the rate at which data is received.

3.) Variety or new unstructured data types (text, video) that require additional processing.

4.) Value or quantitative and investigative techniques used to derive value from data such as recognizing patterns or predicting customer behavior.

It is quite clear that although the benefits of Big Data are numerous, an organization must be firing on all cylinders in order to successfully leverage their Big Data or risk falling behind the competition.