Why the Solution to Data Democratization Is in the Stars

AI is seen by many as the best way to secure the future of their organisations, but there is significant public concern about its possible detrimental impact. Some are concerned about the concentration of power in the hands of huge tech companies, while some see automation as a threat to their employment.

In this 30 minute demo, you'll see a demo of how easy it is to connect to Yellowbrick data warehouse from MicroStrategy, query tables with billions of rows from a TPC-DS workload, and see results in milliseconds or seconds.

Roche, as a leading biopharmaceutical company and member of the Pistoia Alliance, has a diverse and distributed ecosystem of platforms to manage reference data standards used at different parts of the organization. These diverse reference data standards include ontologies and vocabularies to capture specifics of the research environment and also to describe how clinical trial data are collected, tabulated, analyzed, and finally submitted to regulatory authorities. In the context of the EDIS program, Roche has bridged these parts to improve reverse translation from studies into research and also embraced FAIR to emphasize machine-actionability and data-driven processes.

With data coming from so many different sources nowadays (both old and new, both internal and external), it is inevitable that data will arrive in many different structures, schema, and formats, with other variables for latency, concurrency, and requirements for storage and processing. When data types are extremely diverse and combined, we now call it “hybrid data.” This usually drives users to deploy many types of databases and different platforms to capture, store, process, and analyze the data, which in turn results in hybrid data management architectures.