5 myths about Big Data

5 myths about Big Data

How to keep your expectations and understanding of Big Data and its possibilities clear

Big Data has every ingredient that makes it a concept prone to misconceptions. It is relatively new, is a composite market that is build up of smaller technology blocks-each developing at its own maturity curve, and Big Data is the current hype.

Here is what IT leader and analysts have to say about separating the wheat from the chaff and keeping one's expectations and understanding of Big Data and its possibilities clear.

1. Big Data is about unstructured data:

Analyzing unstructured data from social media sites, for example, doesn't sum up Big Data. "A company that's struggling with large volumes, high velocity, or variety of data is an organization having a Big Data problem," says Sid Deshpande, senior research analyst, Gartner.

Take Rajeev Batra, CIO, MTS, for example. Privacy laws don't allow him to peek into customers' Facebook accounts. But his systems process information from 110 TB of structured data everyday to provide better customer service.

2. The biggest benefit of Big Data is better customer service:

The most compelling cases of Big Data have come from companies that have used it to improve customer service. But Gartner has found that this isn't the biggest benefit derived from Big Data.

"When we asked some of the largest enterprises about the benefits they wanted to derive from big data, process efficiency topped the list. This was followed by identifying areas of security risk, and finding new areas of customer satisfaction," says Deshpande.

3. Big Data is an IT project:

Sure, big data cannot impact the bottom-line. But it does provide intelligence that the business needs to act on to derive successful business outcomes. Which is why, it can't be bracketed as an IT project. "If you deal with big data as an IT project, then it is destined to fail," says Michael Chui, principal, McKinsey Global Institute.

Srinivas Peddada, CIO, SKS Microfinance, agrees. "That's the base note. If your business is not on your side for a big data project, it becomes an IT project and it all goes downhill from there," he says.

4. Big Data is a huge initiative:

It doesn't have to be. Nat Malupillai, director, digital analytics, Target India, and Manish Bahl, VP and country manager, Forrester India, say CIOs should not get bogged down by Big Data. CIOs who aren't sure about how to embrace Big Data, or are skeptical about investing in it can always start small.

"To begin with, CIOs can pick a small set of data (say 10-20 percent), be it structured or unstructured, and use the service of a data analysis firm to analyze that data," says Malupillai.

5. Big Data is all about analytics:

Analytics is just one part of Big Data, essentially the end-goal. You need to first figure out how to store, manage, archive, and retrieve data. But often, all this gets buried under the fancy tag of analytics. Big Data can get out of control quickly since discovering value from a slice of data makes you greedy for more data.

Big Data can get too complex too fast. The key is to keep Big Data small and reasonable, and figure out how to manage it before analyzing it.

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