Human-Proofing Sensitive Data Governance with Automated Data Classification

whitePaper | February 7, 2020

The problem is that growing volumes of data can lead to data paralysis, because no one knows quite where to begin or how to use it. Siloed information sources, no data management strategy, disconnected spreadsheets or analytical tools and poor data quality all work to compound the issues you’re facing.

whitePaper | November 10, 2022

In this hyper-competitive era, faster time-to-market plays a vital role in the success of an organization. Any lag accounts for the 'Cost of delay,' impacting the value a product could create otherwise. This is the primary reason teams are adopting an agile approach to software development, testing, and release. Unfortunately, teams that don't follow suit find it challenging to deal with this accelerated timeframe.

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 | September 22, 2022

This report introduces the Climate Data Steering Committee (the Committee or CDSC)’s proposed recommendations for the development of an open data utility for climate transition-related data: the Net-Zero Data Public Utility (the Utility or NZDPU). The Utility is designed to be built as part of ongoing enhancements to the United Nations Framework Convention on Climate Change (UNFCCC)'s Global Climate Action Portal and will therefore also support increased integration of private sector commitments and actions within the UNFCCC stocktaking and recognition processes.

whitePaper | January 31, 2020

Many companies have invested heavily in specialized enterprise data warehouses (EDW) and Extract, Transform and Load (ETL) technologies to analyze their operational data. But these technologies were never designed to be truly real-time.They were originally built for batch, and that original design limits how real-timeEDWs and ETL can become. They were also designed to support a focused group ofanalysts, not a larger group of employees spanning operational functions, or even partner and end customers.

whitePaper | October 21, 2022

Connecting high-quality data assets to the consumers who depend on them unleashes new possibilities for creating more business value.