Systems | Development | Analytics | API | Testing

Data Vault Techniques on Snowflake: Streams and Tasks on Views

Snowflake removes the need to perform maintenance tasks on your data platform and provides you with the freedom to choose your data model methodology for the cloud. When attempting to keep the cost of data processing low, both data volume and velocity can make things challenging.

SCIM (System for Cross-domain Identity Management)

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.

DataOps Observability Designed for Data Teams

Today every company is a data company. And even with all the great new data systems and technologies, it’s people—data teams—who unlock the power of data to drive business value. But today’s data teams are getting bogged down. They’re struggling to keep pace with the increased volume, velocity, variety, complexity—and cost—of the modern data stack. That’s where Unravel DataOps observability comes in.

Our reflections on the 2022 Gartner Magic Quadrant for Data Integration Tools

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.”

Real-time Event Streaming For Customer Data | RudderStack

In this episode of “Powered by Snowflake,” host Daniel Myers sits down with RudderStack’s Head of Customer Engineering, Lewis Mbae. RudderStack helps customers ingest, transform, and integrate data into the Data Cloud. This conversation covers the value of the Data Cloud as a central source of truth, the challenges of building an enterprise-grade customer data platform, empowering data engineers, and more.

Data Mesh Architecture Through Different Perspectives

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.

DataOps Observability: The Missing Link for Data Teams

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.

Adverity is Powered by Snowflake-and Moving into New Markets with Confidence

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.

Introduction to Datastream for BigQuery

Datastream is a serverless and easy-to-use change data capture and replication service that makes it easy to replicate data from operational databases into BigQuery reliably and with minimal latency. In this video, Gabe Weiss, Developer Advocate at Google, discusses setting up real-time replication from Cloud SQL to BigQuery. Watch along and learn how to get started with Datastream for BigQuery!

A Flexible and Efficient Storage System for Diverse Workloads

Apache Ozone is a distributed, scalable, and high-performance object store, available with Cloudera Data Platform (CDP), that can scale to billions of objects of varying sizes. It was designed as a native object store to provide extreme scale, performance, and reliability to handle multiple analytics workloads using either S3 API or the traditional Hadoop API.