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4 Myths People Hold About Big Data

November 25, 2016 |
Big Data

The concept of Big Data is not very new and has been in the air for the last decade or so. The only difference is that the real sense of Big Data has evolved a huge deal over the years. In yesteryears, documents and email data stored in gigabytes were considered to be big data. However, the meaning of big data has completely changed now. One might be required to run multiple SQL queries and think of tricks to pull down a week of summary data without having it choke or overflow Excel. You might have heard a lot of people saying “Every company is a big data company now”. Well, turns out this is the biggest misconception people carry. So, here are 4 common myths busted about Big Data which may give you a real sense of the concept:

1 . Every Data Is Big Data

Big data must be really BIG. It should be high-velocity, high-volume, and/or high-variety data. It simply means that if your data can squeeze in an Excel file, then you’re not dealing with big data. Similarly, if you’re handling a dataset that quantifies in gigs and your computer can handle it, again you’re not playing around with big data. It could be a case wherein you’re dealing with a lot of gigabytes of emails and you don’t have a clue on how to deal with it. But that doesn’t mean that i’s big data.

2. Big Data Is The Solution For Any And Every Problem

People believe that big data fixes everything. Many of them run for big data analysis to solve problems rather than using common sense. Just to quote an example – A few executives were reviewing week-over-week website visit figures and sales. They noticed that the numbers had dipped abruptly during a week in April. However, that same week last year they hadn’t experienced the same decrease. They called for analysis after analysis until someone pointed out, “It is a common trend. We see a decline around Easter every year. Easter is in April this year but was in March last year.” Big data and analysis didn’t help here, but a calendar and common sense did.

3. Big Data Is Meaningless

The biggest misconception is that big data doesn’t matter. Well, it doesn’t if you can’t extract insights out of it or use it to boost your systems. Often executives learn about big data but seldom learn anything from it.

To make big data meaningful, you need to be able to process and use it. Big data companies make this process easier. They gather the data, clean it up, organise it, and output it in a way that data scientists or other systems can process. Once a data scientist pulls stories out of the data or your systems use data to execute business operations like supply chains, executives will start noticing value in big data.

4. Only Big Companies Require Big Data

Another myth about big data is that only big companies should play with it. Even small marketing companies need keyword search numbers and website traffic. Small shopping firms need links to as many products as possible from the large retailers. Small on-demand delivery services need dependable location data. These are only a few examples from the huge list of small companies that require big data.

Almost every company in our modern economy uses big data or apps developed on it. All the companies can get the benefit of access to information and insights of these huge datasets. That too without building and managing the infrastructure required to create and analyse big data.

You can run, you can hide, but you can’t escape big data in business these days. Irrespective of the size of your company. Executives must understand the complexity, dangers, and power of big data in order to make better decisions and run their businesses more efficiently.

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