What’s New in the HAProxy Data Plane API 2.5

As organizations move into the cloud, the choices for handling high-scale data for analytical use are flourishing and evolving. How do we address BI/analytics, data science, security/application monitoring, and log data management workloads? Do we really need potentially overlapping warehouse, data lake, and security and observability capabilities on top of object storage, or can an evolved data lake or emerging “lakehouse” platform do it all? Join Doug Henschen, VP and principal analyst at Constellation Research and Thomas Hazel, Chief Technology and Science Officer at ChaosSearch for a broad-ranging discussion on the challenges and strategy considerations that go into choosing the right platform.

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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.

In companies today, numerous documents are in circulation. Yet the data inside needs to be captured so it can be used for further processing. Just think about how the Finance team needs access to data in invoices. Or how the market analytics department needs access to utility bill data to perform market research. Brokers who need to retrieve data from purchase orders, IT departments that require data extraction as a part of a paperless workflow. The list goes on.