Directory Image
This website uses cookies to improve user experience. By using our website you consent to all cookies in accordance with our Privacy Policy.

Big data's top5 myths

Author: Swapnil Chaudhary
by Swapnil Chaudhary
Posted: Sep 07, 2017

Ever since the name - Big Data was coined to express the mix of structured and unstructured data, which several businesses have been exploiting to get useful information, a lot of mystery and hype have got associated with it. While Big Data has proved to be beneficial to most businesses that have used it, has it really matched the hype that it has generated in its wake? Inevitably, as it often happens with transformational innovations, some myths have also emerged about big data. Let's consider the top 5 myths and see if those need to be debunked.

Myth #1: Big Data is Really Big

How big is big? It is really subjective. The fact that Big Data is generated real time from all manner of sources and sensors, and also includes pictures, audio and video; makes it rather big. If we simply compare this data volume with the structured data that the organizations had hitherto maintained in spreadsheet and relational databases, then it is many times larger. But, more than big, it is diverse and unstructured data. That’s what makes it challenging to capture, store and process it and derive benefits for the organization, be it a business or government or a project/mission. So, the Big Data may not always be humungous in volume but it is diverse and complex, and is very useful too.

Myth #2: Big Data is Good Data

Yes, Big Data is very useful and has started to provide competitive advantage to several businesses. But, is all of the data in Big Data good. The answer is no. Big Data has many errors and also has missing data. Consider for example, some teenagers who upload feedback using slang, which may be confusing as to whether it is positive or negative. They may also wrongly tag some pictures and video. Such data is likely to mislead and create errors, and may need an intelligent model to sift through the data before analysis. It is thus important to include only those data sets for analysis, which may appear more relevant.

Myth #3: In Big Data the Analyst Is the God

Data is too big and getting bigger by the day thanks to high volume, high velocity and variety (granularity). A team of analysts won't be able to handle all of the data in a few years from now. We do therefore need continual development of tools for the users/ marketers to do their own first level of analysis. The expert analysts would be needed only for deeper analysis and providing the larger picture. With emergence of analytical tools, the pre-eminence of data specialist is already on the wane. So, a good balance needs to be maintained between human analysts and analytical tools. The former too is part of the system and far from being God.

Myth #4: Big Data Is Only for Big Businesses

Just like the big businesses have more advertising and marketing spend, they do spend more on market analysis too, which is one of key applications of Big Data. So, having a team of data analysts, along with supporting analytical tools, is de riguer for a large business. However, smaller businesses too can make a start with inexpensive tools and also use cloud computing to benefit from Big Data.

Myth #5: Machine Algorithms Will Replace All Human Analysts

Good data analysts have domain experience and well developed analytical skills. But they can’t perform all of the analysis tasks all by themselves without the support of analytical tools or machine algorithms. The opposite view that human analysts would be completely replaced by analytical tools or machine algorithm is equally without basis and thus is a myth. No doubt that the cost of hiring data analysts is going up and tools for analysis are continually getting better and cheaper. But, the human insight and judgment are invaluable and complex, and can’t be fully incorporated in machine algorithms. Further, apart from interpreting data, a data analyst also provides explanation and may even recommend corrective action. Machine algorithms can’t do that yet.

In conclusion one could say that myths do build around something that is big and transformational, which Big Data has already proved to be. It is up to the businesses to use this beast or genie to their competitive advantage. The race is already under way and new businesses are joining it every day. Want to join the Big Data industry, 3ri Technologies is the best training center for Big Data Training in Pune. We also offer other relevant courses, to know more click here.

Rate this Article
Leave a Comment
Author Thumbnail
I Agree:
Comment 
Pictures
  • nandhinidevi  -  4 years ago

    Data Science with Python Training in BTM UI and UX Training in BTM Angular training in BTM Web designing Training in BTM Digital Marketing Training in BTM

    8
Author: Swapnil Chaudhary

Swapnil Chaudhary

Member since: Sep 07, 2017
Published articles: 1

You have an error in your SQL syntax; check the manual that corresponds to your MySQL server version for the right syntax to use near 's top5 data') >= 2 )AND (i.`status`=2) ' at line 6