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Now on-demand: Data + AI Summit sessions for data architects, engineers, and scientists

databricks

Thousands of data architects, engineers, and scientists met at Data + AI Summit in San Francisco to hear from industry luminaries like Fei.

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How PepsiCo established an enterprise-grade data intelligence platform powered by Databricks Unity Catalog

databricks

This blog is authored by Bhaskar Palit , Senior Director, Data & Analytics, PepsiCo, and Sudipta Das , Data Architect Senior Manager, PepsiCo.

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Introducing Polaris Catalog: An Open Source Catalog for Apache Iceberg

Snowflake

This leaves data architects and engineers with the difficult task of navigating these constraints and making difficult trade-offs between complexity and lock-in. In an effort to improve interoperability, the Apache Iceberg community has developed an open standard of a REST protocol in the Iceberg project.

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Snowflake Advanced Certifications: Level Up to SnowPro Advanced and Show Off Your Snowflake Expertise

Snowflake

“The Advanced Architect badge is a real differentiator between those who have taken an instructor-led course and passed the SnowPro Core exam and someone who has years of experience and a deeper technical understanding of the Snowflake platform — and I’m glad Snowflake has recognized this by developing these advanced exams.”

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Simplify Application Development With Hybrid Tables

Snowflake

“Serving promotion treatment from Hybrid Tables reduces point lookup latency and allowed us to maintain unified governance by keeping all of that sensitive data within Snowflake,” says Rahul Jha, Senior Data Architect at William Hill.

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Telecom Network Analytics: Transformation, Innovation, Automation

Cloudera

Advanced predictive analytics technologies were scaling up, and streaming analytics was allowing on-the-fly or data-in-motion analysis that created more options for the data architect. Suddenly, it was possible to build a data model of the network and create both a historical and predictive view of its behaviour.

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Fundamentals for Success in Cloud Data Management

Cloudera

Everybody needs more data and more analytics, with so many different and sometimes often conflicting needs. Data engineers need batch resources, while data scientists need to quickly onboard ephemeral users.