If you’re a data scientist or you work with machine learning (ML) models, you have tools to label data, technology environments to train models, and a fundamental understanding of MLops and modelops.

Most data management professionals would acknowledge that there is a data life cycle, but it is fair to say that there is no common understanding of what it is. If you Google “Data Life Cycle” you ...

ZURICH & AUSTIN, Texas--(BUSINESS WIRE)--KNIME, an open source data analytics company, today announced the availability of “Guide to Intelligent Data Science; How to Intelligently Make Use of Real ...

Recent advancements in technology, data availability and changing consumer preferences have opened new opportunities for insurers to leverage data and insights. This allows them to enhance operations, ...

SAN MATEO, Calif., Feb. 10, 2020 – dotData, the first and only company focused on delivering end-to-end data science automation and operationalization for the enterprise, today announced that it will ...

Moving data science into production has quite a few similarities to deploying an application. But there are key differences you shouldn’t overlook. Agile programming is the most-used methodology that ...