Systems | Development | Analytics | API | Testing

Value Stream Management (VSM) is about empowering delivery organizations to measure, mitigate, and monitor complexity. Simply put, it aims at improving the flow of value in your organisation. The VSM Consortium recently released their highly anticipated report on “The State of Value Stream Management 2022” . In this post we recap some of the findings and look at it specifically from a software engineering and platform engineering point of view.

The identity team at Cloudera has been working to add the System for Cross-domain Identity Management (SCIM) support to Cloudera Data Platform (CDP) and we’re happy to announce the general availability of SCIM on Azure Active Directory! In Part One we discussed: CDP SCIM Support for Active Directory, which discusses the core elements of CDP’s SCIM support for Azure AD.

What if I want to serve a Huggingface model on ClearML? Where do I start? In general, machine learning engineers know by now that a good model serving engine is invaluable when serving models in production. These days, NVIDIA’s Triton inference engine is a popular option to do so, but it is lacking in some respects.

This is a guest post for Integrate.io written by Bill Inmon, an American computer scientist recognized as the "father of the data warehouse." Inmon wrote the first book and first magazine column about data warehousing, held the first conference about this topic, and was the first person to teach data warehousing classes.

In its 2022 Magic Quadrant™ for Data Integration Tools report, Gartner® observes that “organizations are increasingly seeking a comprehensive range of improved data integration capabilities to modernize their data, analytics and application infrastructures.”

Is your small business struggling with inflation? Not sure whether to cut costs or optimize spend? We’ve analyzed 55 small businesses in an attempt to help you solve this dillemma.

What’s harder than finding the right data architecture? Finding the right dedicated partner. Adverity gets both with Snowflake. Learn how the two organizations are moving into new markets and supplying even more reliable marketing data to Adverity customers. When a fast-growing SaaS business looks to expand its client base, it normally encounters two major challenges: In many cases, an external data solution provider can only help solve the scalability challenge.

As organizations invest ever more heavily in modernizing their data stacks, data teams—the people who actually deliver the value of data to the business—are finding it increasingly difficult to manage the performance, cost, and quality of these complex systems. Data teams today find themselves in much the same boat as software teams were 10+ years ago. Software teams have dug themselves out the hole with DevOps best practices and tools—chief among them full-stack observability.

We previously wrote how the data mesh architecture rose as an answer to the problems of the monolithic centralized data model. To recap, in the centralized data models, ETL or ELT data pipelines collect data from various enterprise data sources and ingest it into a single central data lake or data warehouse. Data consumers and business intelligence tools access the data from the central storage to drive insights and inform decision-making.