Data Storage, ASEAN: Cognizant’s Vice President and APAC Head Says Companies Need a “Fish-Finder” to Catch Business Insights From Volumes of Continuously Generated Data

“Building semantically-rich information architecture is becoming increasingly crucial to help businesses see hidden patterns in the fast-proliferating data pools that surround people, organizations and devices,” writes Jayajyoti Sengupta. “Indeed, to cut through the clutter and compete in the market, companies need a fish-finder to catch business insights from the volumes of data continuously generated by people, products, processes and organizations, which produce unique digital identities.” Excerpts:

“As the number of connected devices grows ten-fold to 100 billion, data volume is expected to double every two years to 44 zettabytes or 44 trillion gigabytes, by 2020. This data growth is not only inevitable, but also essential to creating and improving all-important algorithms to create better, more personalized experiences for customers through managing and deriving actionable insights from the sheer bulk of data.

Semantic technology lets you build on and extend your data warehousing and big data investments to drive much more powerful insights from a much broader data set more quickly.

Think of all the data from all your sources, internal and external, old and new, flowing into a massive “data lake”. As the lake gets bigger and bigger, with more and different types of data, how do you effectively identify and gather the data you need?

The data has to tell you itself. What you need is the data equivalent of a fish-finder that can peer into the dark depths of the data lake and tell an old sunken tree from a school of prized game fish.

This “fish-finder” for business insights is here, in the form of a smart, semantic model that captures the meaning of data, as well as the related domain expertise from data (whether it is structured, unstructured or semi-structured).

More importantly, generating meaning is essential—we need to know what the data means and what it represents before we can use it in algorithms that deliver business and user benefits.

An intelligent semantic model can deliver meaning and intelligence that empowers better decision-making.

This semantic model also helps identify the data needed to craft more personalized customer experiences. A semantic model makes it easier to embed domain expertise—field-based insights into how your customers, products or markets work—into the data.

Building this “fish-finder”—an intelligent semantic model that sits on top of your current information architecture—probably sounds daunting. But it can be done, starting with important but gradual changes that include prioritizing the onboarding of data, and balancing legal and compliance needs for security, with the imperative to improve the customer experience through analytics.”

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