How can Big Data Testing for Pharma Sector Boost Innovation?

Big Data testing

According to a joint study by recruitment consultancy Robert Walters and Jobsite, 47% of recruitment Managers have anticipated increased demand for IT workers in 2017. The findings from the survey of 700 senior technology professionals indicated a rising demand for Business Intelligence (BI) and Big Data professionals.

As per the report estimates, 2017 will see a soaring demand for Big Data and Cyber Security experts/professionals. The reasons are obvious – there is increasing awareness amongst enterprises about the benefits that they can reap from Big Data Analytics tools and skills.
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The opinions expressed in this blog are author's and don't necessarily represent Gallop's positions, strategies or opinions.

5 Big Data Testing Challenges You Should Know About


5 Big Data Testing Challenges You Should Know About

Enterprise data will grow 650% in the next five years. Also, through 2015, 85% of Fortune 500 organizations will be unable to exploit Big Data for competitive advantage. – Gartner

Data is the lifeline of an organization and is getting bigger with each day. In 2011, experts predicted that Big Data will become “the next frontier of competition, innovation and productivity”.   Today, businesses face data challenges in terms of volume, variety and sources. Structured business data is supplemented with unstructured data, and semi-structured data from social media and other third parties. Finding essential data from such a large volume of data is becoming a real challenge for businesses, and quality analysis is the only option.
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The opinions expressed in this blog are author's and don't necessarily represent Gallop's positions, strategies or opinions.

2 Major Challenges of Big Data Testing

2 Major Challenges of Big Data Testing

We all know that there are umpteen number of challenges when it comes to Testing – lack of resources, lack of time, and lack of testing tools. The industry has faced, probed, discovered, experimented and found its way out of most of the challenges of data testing. Having trumped so many challenges you would think developers can now sit smug and relax.
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The opinions expressed in this blog are author's and don't necessarily represent Gallop's positions, strategies or opinions.