The Definitive Guide to Test Data Management

whitePaper | December 13, 2022

Modern Data Analytics Platforms (DAP) have gone through rapid architectural pattern changes over the past few years, independent of the use cases, to provide maximum benefits to the consumers.

whitePaper | November 23, 2022

Artificial intelligence (AI) and machine learning (ML), along with data analytics, are widely seen as a way to tackle everything from daily inefficiencies and low productivity, to advancing healthcare and climate change mitigation. As more organisations look to leverage their data more effectively, demand for people with data capabilities is only going to grow

whitePaper | December 5, 2022

When modern LIMS software overtook traditional paper-based record-keeping in the lab, operations in every industry improved. Automated data collection drove efficiencies at the bench. Cloud solutions accelerated knowledge-sharing between partners. Built-in security and permission features enhanced data integrity. There’s hardly a lab in operation right now that hasn’t gained from this leap towards digital transformation.

whitePaper | October 10, 2022

Companies undergoing digital transformation must make data available to all stakeholders. However, outdated security and governance tools can prevent companies from freeing their data without opening themselves up to new risks.

whitePaper | June 16, 2022

It seems like the business world has gone crazy for machine learning (ML) and artificial intelligence (AI), viewing the technologies as the essential keys to the very future of the enterprise. In fact, a recent survey from ESIThoughtLab found that two-thirds of business leaders see AI as critically important for their future. And yet, the respondents report that only 25% of AI projects are in widespread deployment and 40% of all projects are generating negative or no returns.

whitePaper | June 24, 2022

The reactive approach to discovering, analyzing, and correcting data quality issues in business applications has been marginally effective throughout the era of data consolidation for analytics (data warehousing, etc.) and the subsequent onset of “big data.”