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.
Read More

The opinions expressed in this blog are author's and don't necessarily represent Gallop's positions, strategies or opinions.

Is your Enterprise Big Data Tested?

Is your Enterprise Big Data Tested

The Startup buzz is gaining grounds and it has transformed the way enterprises strategize and operate. Startups are known to leverage various technologies that boost cost effectiveness, efficiency and time to market. For instance, thanks to the Open source platforms, today Startups have access to the best Big Data infrastructure and testing tools at ‘zero’ cost. They run a mile further in optimizing the Cloud to reap the most from their Big Data investments.
Read More

The opinions expressed in this blog are author's and don't necessarily represent Gallop's positions, strategies or opinions.

Moving from Descriptive Metrics to Predictive & Prescriptive Metrics

Descriptive metrics to predictive and prescriptive metrics

 

With the deluge of data being churned every day in businesses, organisations are turning to analytics solutions to understand what these huge volumes of data mean, and how can they help improve decision making. We need to chart a new course with data, which is to predict.

Every organization that is driven by data wishes to fulfil its promise of doing it right. Reviewing the available analytic options in itself can prove to be a humongous task in itself. Analytics are necessary when data is needed to answer specific business-related questions, whereas through metrics it’s being responsible to a certain action and in order to measure, metrics are formulated from the analytics available.
Read More

The opinions expressed in this blog are author's and don't necessarily represent Gallop's positions, strategies or opinions.

10 Signs You Need Help With Big Data & Analytics Testing

10 Signs You Need Help With Big Data & Analytics Testing

Many industries, of late have decided to venture into the new world of Big Data and Analytics. They are slowly beginning to fully understand the limitless benefits that Big Data unearths for them, but a lot of enterprises are also struggling to deduce useful information from their Big Data programs. Many missteps made by a company are due to the fact they haven’t tested their Big Data processes and protocols thoroughly.
Read More

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.
Read More

The opinions expressed in this blog are author's and don't necessarily represent Gallop's positions, strategies or opinions.