Nikunj Thakkar Tech Expert

Nikunj is the CEO of DataOne Innovation Labs. His company provides architectural solutions for big data problems faced by enterprises. His main areas of focus are real-time data processing, machine learning, NLP, cloud computing and high availability architecture design. Nikunj holds a master’s degree in Information Technology from the Dhirubhai Ambani Institute of Information and Communication Technology.

 

Big Data in E-Commerce: Trends, Personalisation and Beyond

E-Commerce, as an industry, received a jump start because of the progress made by big data engines in providing critical and focused analytics to retailers.

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Big Data in Startup/SME Environment

Previously, we spoke about the role of Big Data in Healthcare, and the response to the article has been nothing but phenomenal. This time, we have decided to tackle a whole section of the work environment that really links up with Big Data, giving shape to the Big Data Industry as well as truly utilizing what Big Data has to offer. In this article, we are going to discuss the impact of Big Data on the Startups and Small-Medium size Enterprises (SMEs).

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Big Data in Telecom: A Big Bubble or A Big Opportunity?

As the Telecom industry goes through phases of troughs and crests, the one constant that marks the industry is the abundance of the types and volumes of data that it has. While the industry had great expectations of Big Data in the initial years, this vibrancy was followed by a period of doubt. Now, as things look up again, let us see how the trends have evolved over the last six years.

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Big Data in Healthcare Industry

In a previous article, we introduced Big Data, defined what is, its market presence, and its role in creating social good. Continuing along the same lines, we will talk about another field in which Big Data is playing a big role: The Healthcare industry.

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Big Data: A State of the Union

Big Data. The keyword of the decade. Yet, it’s barely understood or often confused by so many. The idea behind Big Data is simple. Collect all the data you can (Volume), from multiple sources in any and all formats (Variety), as fast as you can (Velocity), and try to be sure the source provides useful, accurate and clean data (Veracity). The 4 V’s just mentioned, form the basis of Big Data.

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