Contextualizing Big Data For The Everyday Business

In Big Data by Daniel Newman5 Comments

Words like terabyte, petabyte, exabyte, and zettabyte among many others have entered the business lexicon holding the hands of big daddy – yes, we’re talking about big data here.

As data is growing at a monstrous speed, businesses are left grappling on how to curate data or how to even make sense of it. According to a Gartner report, through 2015, 85% of the Fortune 500 companies will fail to exploit big data for competitive advantage. As extraction of data becomes difficult, organizations will have to develop resources and strategies to tap into the unlimited potential of big data or else they can never really gain from the info-thick big data that holds the golden key to future success.

Harness the power of data to maximize relevance

When pulling out information from the huge data pile, our main focus should be on data that’s relevant to our business. Big data holds a sea of precious information which includes customer behavior, market demands, changing needs, shifting preferences, and more such valuable insights that could help businesses grow and adapt to the changes quickly. To build this capability, businesses will need to improve their network infrastructure, reinforce their analytical abilities and enhance the intelligence of their business operations. To fully understand the scope of integrating big data analytics in their framework, businesses have to look deep down within their operations, processes and databases.Contextualization comes as a second step to this.

Build contextualization through three data types

Demographic data

This type of data explains who the customer is in big, bold words. Customer preferences, purchase patterns, behaviors, concerns, and their interaction with digital channels give businesses a clarity on the nature of their customers.

Historical data

Past records of customer interaction, whether they made purchases, whether or not they were satisfied – all of these fall under the category of historical data. Such information can be gathered from the data trail that customers leave when they interact with any company while visiting the website, spending time on various product pages or making purchases. This data acts as a way to predict the behaviour and future actions of customers.

Situational data

The current geographic location of the customers, devices used by them, their current online activities etc. help organizations gain an idea of what are the current preferences of the customers or what are they looking for at a particular time.

These data types help business gain full context of every customer interaction. Moreover, categorizing data helps to systemize the process of data mining and comprehension so that the information can be used in the most effective manner.

Today when big data has become an essential for companies, they should be able to make sense out of it in order to utilize its benefits.Contextualization not only helps to comprehend the data in the best possible manner but it also helps in gathering and storing data in ordered groups and sequences. Once this process is in place, organizations can use big data to unlock various key insights that will help them prepare their businesses for the future.

Disclaimer: This blog was written as part of the Connect With Ricoh Innovative Ideas program and was first seen here. While I was compensated for this post, the ideas and views are my own. 

Daniel Newman is the Principal Analyst of Futurum Research and the CEO of Broadsuite Media Group. Living his life at the intersection of people and technology, Daniel works with the world’s largest technology brands exploring Digital Transformation and how it is influencing the enterprise. From Big Data to IoT to Cloud Computing, Newman makes the connections between business, people and tech that are required for companies to benefit most from their technology projects, which leads to his ideas regularly being cited in CIO.Com, CIO Review and hundreds of other sites across the world. A 5x Best Selling Author including his most recent “Building Dragons: Digital Transformation in the Experience Economy,” Daniel is also a Forbes, Entrepreneur and Huffington Post Contributor. MBA and Graduate Adjunct Professor, Daniel Newman is a Chicago Native and his speaking takes him around the world each year as he shares his vision of the role technology will play in our future.


  1. Since I have worked for “big companies” and seen them in action I disagree with Garnter. I feel/seen “big companies” invested heavily in harnessing big data in traditional ways using SQL etc. Yes there is a lot of opportunity must most of them are very expensive with no assured return. I agree Contextualization is a great idea but it is very difficult to get clean sources of data that are compatible and Joined together.

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