Reliable data replication in the face of schema drift
Learn methods for ensuring that data replication remains robust even as schemas change.
Learn methods for ensuring that data replication remains robust even as schemas change.
Feature engineering is a crucial part of any ML workflow. At Continual, we believe that it is actually the most impactful part of the ML process and the one that should have the most human intervention applied to it. However, in ML literature, the term is often overloaded among several different topics, and we wanted to provide a bit of guidance for users of Continual in navigating this concept.
Our valued partner, Deltek is a leading provider of software and information solutions for project-based businesses. Headquartered in Herndon, Virginia, the company leverages its expertise to maximize efficiency and revenue for clients through project intelligence, management, and collaboration.
Whether the enterprise uses dozens or hundreds of data sources for multi-function analytics, all organizations can run into data governance issues. Bad data governance practices lead to data breaches, lawsuits, and regulatory fines — and no enterprise is immune.
The keynote presentation at DataOps Unleashed 2022 featured a roundtable panel discussion on the State of DataOps and the Modern Data Stack. Moderated by Unravel Data Co-Founder and CEO Kunal Agarwal, this session features insights from three investors who have a unique vantage point on what’s changing and emerging in the modern data world, the effects of these changes, and the opportunities being created.
At the DataOps Unleashed 2022 conference, Luis Carlos Cruz Huertas, Head of Technology Infrastructure & Automation at DBS Bank, discussed how the bank has developed a framework whereby they translate millions of telemetry data points into actionable recommendations and even self-healing capabilities.
You have dedicated tons of man-hours to building your product and strengthening your service. You are trying to ensure that your application is useful but, above all, that it succeeds at making users come back for more. But then, *gasp*, they don’t! Why? What went wrong? How can you get them to come back?