Top 5 Trends in Data & BI Governance

whitePaper | August 2, 2022

The volume of data has exploded across all sectors in the last decade. Enterprise data has grown enormously, and organizations must contend with more unstructured data than ever. In fact, 95 percent of businesses cite the need to manage unstructured data as a challenge.

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 | 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 | April 1, 2021

Metadata is more important now than ever. New technologies have enabled businesspeople who have traditionally not been analysts to work with data. The consumerization of IT means people expect systems to be intuitive and require little training. With so many people using data to support so many kinds of decisions, it’s critical that your data is described, defined, and understood.

whitePaper | October 17, 2022

Today, massive amounts of data are collected, processed, and stored for a range of analytical purposes around the world. Every customer, device, transaction, email, and image leaves a data trail. At present, this data is growing too big, changing too fast, and becoming hyper distributed. The traditional ways of doing integration and analytics are no longer viable or scalable. It is not feasible to create millions of data pipelines and to continue moving large amounts of raw data to a data lake or a centralized data warehouse.