POINT OF VIEW: IOT AND ANALYTICS

whitePaper | November 18, 2022

It’s time to treat data like a product, not an afterthought. A new paradigm has emerged among forward-thinking data teams: treat your data like a product. This may sound easy in theory, but it’s far from it! Product development processes have become incredibly sophisticated, with resources dedicated to reliability, adoption, feature roadmaps, and more.

whitePaper | September 12, 2022

This whitepaper examines clinical trial data contribution policies and the data protection methodologies applied to protect patient privacy. Information published by 29 biopharma sponsors was collected across three data-sharing platforms, collated by sponsor size. Results showed that large sponsor contribution policies can provide helpful benchmarks for medium and smaller sponsors.

whitePaper | May 6, 2022

Every organization today recognizes the strategic value of generating actionable insights from their enterprise data.

whitePaper | August 18, 2022

The 2022 data connectivity survey pivots somewhat from prior years’ studies. Data connectivity and data integration are well established in the traditional on-premise computing environment. But we’ve seen that as organizations increasingly expand their domains to one or more cloud service providers, it is important to better understand the challenges and opportunities for connectivity presented by modernization initiatives.

whitePaper | June 23, 2021

Analytical data infrastructure (ADI) platforms underpin key analytics models via processes like data integration, preparation, management, and storage. But with complex cloud architectures, as-a-service offerings, and innovative new analytics and process developments, how can the discerning expert choose the right ADI offerings for their business?

whitePaper | December 9, 2022

In Data Governance Methodology, we described why a modern active data governance methodology is superior to a traditional top-down methodology and how active data governance is supported by continuous improvement. We also discussed how a data governance process based on continuous improvement is a key component of a DataOps process.