Evolving Considerations for Data Storage in Life Sciences

whitePaper | September 28, 2022

By building smarter apps and increasing the speed of business insight, application-driven analytics gives you the opportunity to out-innovate your competitors and improve efficiency. However, it does require a shift in the way we think about and deliver analytics.

whitePaper | October 27, 2022

Data governance is on everyone’s mind as we move from a static model of data to a dynamic, living, breathing data architecture. As many brilliant people have already said, data — and knowledge in general — is full of “ghosts,” or implicit knowledge existing within any organization that never makes it to documentation. Ghosts affect companies in both data and people spheres, making it challenging to modernize legacy architectures or bring new talent on board. Even more, it makes using data a challenge.

whitePaper | October 6, 2022

Effective data analytics provides enormous business value for many organizations. As ever-greater amounts of diverse data become available, analytics can provide even more value.

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.”

whitePaper | November 18, 2022

For decades, the lack of visibility into the health of our data has led to data downtime in companies around the world. When data is missing, inaccurate, or erroneous, data quality initiatives are doomed to fail, leaving enterprises at a privacy compliance and business disadvantage.

whitePaper | July 8, 2022

This series of white papers lays out the essential steps you need to take to ensure your business stays at the forefront of an increasingly data-driven and automated world. We cover everything you need to know about growing a data science team, the current trends in machine learning, data visualisation, essential data science tools and technologies, automation, deployment, how to prove value with data science and also give our thoughts on the next ‘big ideas’ that are set to take the world of AI in business by storm.