Is Really Big Data Getting Too Big?

By Jyoti Nigania |Email | Apr 10, 2018 | 15933 Views

We probably all know that obesity is becoming a big problem in the developed world and just becoming bigger. It's a mindset that more is always better like more food, more choice but that's not always the case. This is a just similar phenomenon that we must choose the right food in the right amount to keep us healthy, same businesses must be judicious about what data they collect and what variety they have.

Big data is the act of collecting large data sets from traditional and digital sources to identify trends and patterns. That collected information is used by the companies to improve what they know about customer's wants and needs.  The goal should be to make solid decisions based on data and not just hunches. Peoples are increasingly willing to hand over their personal data in return for products and services that makes their lives easier.

But what does that mean for you, the source of the data? Well, think of it as a trade. Tweets and Facebook posts are a bit harder to analyze than structured data like store receipts or web traffic. Unstructured text or images require special software to extract their meaning and since the volume of unstructured data is so large many business need to use special hardware just to organize and understand it.

Companies that are on their game use both structured and unstructured data to build up their customer insights each step of the way. Data driven marketing is what it is all about these days, and every organization must know the three V's of analysis if they want to get succeed.

Volume: The amount of data.

Velocity: The speed at which the data is generated.

Variety: The kind of data available.

The more the data the business analyzes the more it can make the experience better of the customer. With big data, more is not always better. Most organizations could probably do with going on a data diet and understanding that they need less data overall, but more specific data that helps them to solve their most important problems.
We don't need more data, we need the right data. Don't wrap up here for detail learning please check out "HOB Artificial  Intelligence".


Source: HOB