Amidst the social, economic and technological revolution swirling around us, how we understand information has assumed even greater importance. Data is deeply embedded in every aspect of our lives from business to leisure and this data can in turn be used to sort out issues and ensure greater prosperity.

Big Data provides insights and the technique to sort out, process and distribute an enormous amount of varied data. Data scientists who create algorithms to draw out valuable information. Despite the obvious benefits of Big Data, it still gets bad press. If we boil down the various misconceptions floating around, we come up with the following:

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1. Big Data is Only for Big Businesses

Big Data technologies may have been exorbitantly priced earlier but it is not the case now; Big Data tools have become inexpensive and are run on efficient commodity hardware. In short, they are accessible and no longer the domain of deep pockets. In fact there are big-data technologies structured for nearly every industry, because most companies, whether big or small, will generate humongous amounts of data that can provide real results. Putting it all in one place can give insights which will optimize your marketing. In the future Big Data will become a vital component of competition because it helps you identify problems and react immediately, thereby saving time and money.


2. Big Data is Unstructured and Complicated

Big Data isn’t rocket science. Big data isn’t complicated because if it was, we would not be using Big Data in our daily lives like when Netflix selects our recommended shows and movies. Despite the sheer volume and velocity of Big Data, an efficiently designed Big Data system can give you information at your fingertips and perceptive insights to benefit your strategy.

On the other hand, simple analytics applied to amassed huge volumes of data can lead to confusion, delay and failure to make beneficial decisions in the long term. Far better than to narrow down the data to the specific business issue and then apply advanced analytics to the data. Data fueled marketing provides a model to provide information from varied data inputs which can then be used to provide relevant messages to clients regularly.


3. Big Data is Just Hype, a Passing Fad

Actually Big Data has been here for more than 20 years but the change has been in the sheer volume of data and the maturity of the ecosystem. Big Data is in the news because it has revealed the ability to hone huge amounts of data to your advantage. It is a whole new ball game for businesses, to address their data requirements in an efficient manner which will in turn lead to an increase in productivity. Big Data is a game changer and those who don’t hitch a ride on it are making a big mistake.


4. Big Data is the Solution to All Our Problems

Big Data can be untidy, noisy, distracting and riddled with inconsistencies. Asking the right questions is vital so that data can be pruned for analysis. There has to be a process in place so you can make sense out of Big Data instead of floundering in data hell. Identify the business issue and then pinpoint the kind of data you need to apply to get to a solution. Big Data requires specialized human interpretation and quality data  to provide comprehensive results. Else, garbage in; garbage out.


5. Big Data is Only for IT Department

Actually Big Data is not just the domain of IT guys; it is also a valuable tool for marketing and sales. You can reap the benefits of data driven insights and make better decisions.


6. Big Data Raises Social and Ethical Questions

Big Data analytics can infringe on civil rights protections in how personal information is utilized. The question is how to benefit from new technology while at the same time protecting fundamental values like privacy and fairness. The balance can shift between those who hold the data and those who are studied in that data. Big data technologies can generate hitherto unperceived insights. But the technical capabilities of Big Data have reached a level of comprehensiveness that requires understanding of how best to balance the opportunities versus the ethical questions raised by these technologies.


Changing for the Better

Dipping your toe into the water before jumping in is good, but one should be clear headed. Changing to a more cost effective model  is desirable as well as required  in today’s fast paced world  and that is where Big Data comes in. There will be always be naysayers who will back up because they don’t like the new temperature of the water or are averse to change.

Hexanika is sure that slowly but surely, the doubting Thomases will be won over as they see the advantages accruing from Big Data. Please reach out to is if you need any help in your journey.


Author: Maheen Usmani

2 Comments. Leave new

  • I agree that “Big Data analytics can infringe on civil rights protections in how personal information is utilized.”
    As more data is brought in, the result is a slow brew of gathering risk without sufficient data security currently included in Hadoop. This situation is slowly improving and a few Hadoop distributions provide sufficient data security.
    To reach the goal of securing the data while preserving its value, the data itself must be protected at as fine-grained a level as possible. Securing individual fields allows for the greatest flexibility in protecting sensitive identifying fields while allowing nonidentifying information to remain in the clear.
    Anonymizing privacy data completely may not be feasible in a monetizing scenario, but deidentifying the most sensitive information, e.g., names, social security numbers, birth dates, is vital to protecting the privacy of individuals.
    Using data protection methods such as tokenization can also allow businesses to preserve the type and length of the data, as well as deidentifying only part of the data fields, while leaving the relevant parts in the clear, such as exposing a birth year rather than the entire date.
    This will keep the data usable for third parties to analyze, while helping to protect the privacy of the individuals who make up the data.
    Ulf Mattsson, CTO Protegrity

  • I agree with your comment since privacy and security are very important features for any big data technology software.


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