Tips For Extracting Insights From Big Data

Published 2017-05-05

One of my earlier blogs gave you a tour of the Programming languages for Data Science. I had mentioned, it was the end of tools of different functional architecture layers. But not the end of Big Data. Knowledge on Big Data is as voluminous as the Big Data itself.

Knowing about the architecture of Big Data and the different tools present in market to work with Big Data is not enough. Big Data domain has much more verticals than we can think of. Almost every week a new development takes place.

But I will keep it simple to begin with. Here are the most basic and useful tips for extracting Insights from Big Data.

The main purpose behind the whole picture of Big Data has been about the insights we could derive from the Big Data. The insights which could prove to be of great help

in analyzing the present value of your business
in predicting the future growth of your business
in strategizing the ways which could benefit your business
in knowing the need of the huge army of consumers

And the list goes on. There are some things which we should keep in mind while we are extracting the valuable insights from the Big Data.

Below is the list of some strategic tips to follow before starting with your insight extraction process.

Use Clean Data –

Whatever insights we derive form the data is all because of the data we have to put into the analyzing process. Hence, it becomes all the more important that we are collecting the right data. And with that it is equally important that the data entered into the analytics engine is completely well-organized and most essential. With this it is also necessary for businesses to generate and store as much data as possible. It is good to have more data in hand before drawing any conclusions from the insights.

Use multiple data sources to get the whole picture –

We all know every year every business generates lots of data that if analyzed properly generates deep insights which could prove to be beneficial for business plans. But we need to look at the bigger picture to understand Big Data. Of all the data that is present in the world, a single company’s data forms just the fragment of it. Hence, the results drawn from it will only give you a partial view of what’s going on in the world.

Well, it is not at all a cumbersome task, the right tools and processes could help you monitor and manage multiple data streams. By aggregating and linking the data, you can infer relationships with sources that provide you with a more accurate picture of your business market.

Data integrity is a team effort –

The success and failure of data strategy is all dependent upon how the businesses maintain their databases. Every detail related to the business has to be kept up-to-date in order to rely on the information your data strategy provides. We also need to have the live updates from external sources and same is for internal data sources. Maintaining the data is the responsibility of all the people in the business like the IT team, frontline sales people and everyone else involved in the process.

Aggregated data can tell you anything, if the query is structured properly –

Collecting and storing all the data of business is not just enough. And taking a broader view of it for analysis is also not enough. The data which you have in hand could tell you a lot many things than you would have actually thought of. But the whole game revolves around how you are querying your data to extract insights from it.

Data Scientists say that data analytics is as much an art as a science. And when it comes to analyzing the business data, the culprit is hidden in the petty details. Hence, it is vital to delve into the details to find the real insights.

Introduce pixel tracking analytics –

The companies should design their websites in a manner that so that it helps them in collecting data related to their marketing ads and of the product sales. It would make the website as a data generating tool rather than just a marketing and sales platform.

There is a methodology called pixel tracking which could generate huge benefits for the company. The IT and marketing departments should work hand in hand to inculcate the pixel tracking on the various websites used by the company whether it’s mobile, a microsite, or another location. Data could be tracked from the social media websites also by using social media pixel tracking. This tracking also provides you the information about the users’ device which could help you in understanding if the sales are coming from mobile or web consumers.

Use Statistical Modelling –

Before developing the TV commercials the Marketers should take advantage of the enhancements in Data Collection which would help them to match their campaigns to actual results. For creating statistical models metrics on the stations, airing size, demographic information, second-screen activity and other should be combined.

Target Specific Demographics –

It is a pre-requisite for marketers to design their strategies around the target group of people, consumers or place. It is necessary to know their search habits, devices they are using and other behavioral metrics in order to leverage more ROI from the data collected from the digital media and TV placements.

Use mixed media modelling –

In order to make better future plans, the best solution for the businesses is to use the mixed media modelling technique. The analysis of sales and response data forms the basis of it. It helps marketers to judge all the distribution channels thoroughly. Hence, they can weed out the underperforming channels and direct more budget to the profit generating channels.

Gauge the retail –

Retailer’s information is the best data which would help in gauging the customer preferences. The data helps you in knowing the correlation between the effects that could be caused by the two actions of the marketing policy. Understanding your customer’s responses can directly help you in increasing the products sales and demands.

We can learn from Amazon on how it makes the best utilization of the Big Data. The way it provides suggestions to the users of products they may like and the way the company processes the millions of transactions and shipments. By analyzing its Big Data Amazon tries to benefit its business in two ways – one is it improves its own processes as per insights and second is it to improve the customer experience.

Amazon is not alone using the technique of improving business progress through Big Data Analysis. Almost all the top notch companies are doing that. Hence, I hope the above tips help you in improving your extraction process and increasing business profits.