Top 5 Myths About Big Data

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Did you know Big Data market revenues worldwide for software and services is estimated to see a steep rise from $42B in 2018 to 4103B in 2027 and thus attain 10.48% Compound Annual Growth Rate(CAGR).

Today, organizations and businesses are making revolutionary advances by learning to combine huge volumes of data available at their fingertips with data science and cutting edge analytics.

As Big Data is a relatively new concept and an evolving technology, there is a lot of myths attached to it. Failing to evaluate these myths with facts can lead to mistakes.

Hence, in this blog I will discuss some of the popular Big Data myths. This will help to ensure that your businesses big data plans stay on track.

Common Misconceptions About Big Data

Big Data Needs A Big Budget

Large organizations including multinational corporations and government are heavily investing in smart machineries and large data centers. They are also aggressively highly knowledgeable and skilled data scientists.  These might make you think that big data implementation is a very expensive process.

However, what you should remember is that because of its increasing relevance, Big Data is becoming more affordable day by day. It’s usefulness has spurred the development of a wide number of services and tools that are aimed at enabling business to crunch through the data as they collect it.

Big Data Concerns Only Those In  IT

Before PC’s became mainstream, the only ones that can be found in an organization was in the IT department. As you can see today, every employee in an organization uses a PC on a daily basis. This is because PC’s became more accessible and cheaper with time. The same thing is going to happen with Big Data. If you keep it within the confines of your IT department, your other parts of business are going to miss out. What you need to remember is that access to data can make most things more efficient and better.

It’s All About The Data Size

Volume is only a single feature of Big Data. Its other characteristics such as velocity and variety is equally important. As Data is coming at a fast pace, the more quickly you are able to process it, the more you will be able to be relevant and up-to-date.

Data is available in different formats. The more variety of data you have, the better it is as it means that you have more ways to look at a problem and come up with innovative solution. The point I am trying to make is its wise to look beyond the size of the data they have and consider the advantages of that a variety and velocity of data can translate for you.

Even if you have large volumes of data, they are rendered futile if they are old, from limited number of sources or unverified. They can also prove to be dangerous as they might complicate simple solutions leading to a drain of expenditure on compliance, storage and capture.

Everybody is Doing It

With the recent hype surrounding Big Data, there is a tendency for everyone to jump on board without considering its implications. Research suggests that the number of companies which has put Big Data into work is really small, implying that for the majority it remains as something that they know they should be doing because everyone is doing it, but have not got it right yet.

The problem here is rushing into Big Data due to the fear of missing out. It’s true that delaying is a pit of its own, however, doing things in a rush is also not the correct way to go when it comes to big data. Spending ample time researching the possibilities of moving to a data-driven business model and developing a strategy, might slow down your entry into Big data and also let your competitors gain a significant lead, but it is the correct way to realize your Big data aspirations.

Big Data Will Help You To Make Accurate Predictions

An important thing to remember is that Data cannot yield an accurate prediction of the future.

Prediction made by analyzing big data is about extrapolating what is the likelihood of something happening in the future, based on what has happened in the past. When you are analyzing real-time data, big data can also help to estimate what can happen in the present as well.

All predictions are based on probability and thus there is always a margin for error. You might think that the more data you have, and more accurate they are, the more chance that your predictions might be right. However, this is not true. Data can only help you to estimate the probability of something happening.

End Note

These are some of the common myths about Big Data. As you can see, some of these are most likely to be accepted as facts by a layman who lacks in-depth knowledge about the field. Thus, before you think of implementing/dismissing Big Data, it is advisable to comb through research papers or journals available on Big Data before you take any action.

About Vibhuthi Viswanathan

Vibhuthi is a an avid follower of the latest trends in the world of Technology. Her writing aims to engage and educate the readers on all things Tech. When she is not twirling with words and pauses at SpringPeople, she binge reads popular literature.

Posts by Vibhuthi Viswanathan

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