Thomson Reuters - Reducing Costs and Delivering Information Faster with Snowflake

Thomson Reuters is one of the world’s leading provider of news and information-based tools to professionals. Their worldwide network of journalists and specialist editors keep customers up to speed on global developments, with a particular focus on legal, regulatory and tax changes. Hear how Thomson Reuters was able to deliver answers to their customers faster and reduce costs with the Snowflake Data Cloud.

Commands: Debug and Property Update

The support of remote issue observation, investigation and possibly resolution is a powerful new feature of Edge Flow Manager. This video shows a case where the user observes a problem via the Agent Manager UI, is able to collect additional information using the Debug Command which provides configuration, property and logs from the observed agent and in this particular case is able to resolve the issue by using the Property Update Command to reconfigure the agent remotely.

What Are The Forecasting Best Practices Of Transformation Leaders?

Finance leaders are facing the most turbulent trading conditions for more than a generation. The odds of recession are rising, US inflation has hit a 40-year peak, the “Great Resignation” has denied organisations the people they urgently need to go to market, stock markets have slumped, exchange rates are beyond volatile and, although abating, there is still the threat of a fresh round of Covid. Forecasting business performance has never been so challenging.

5 Signs of a Rookie Mistake in Data Management

This is a guest post by Bill Inmon, an American computer scientist. Many industry leaders recognize him as the father of the data warehouse. Inmon authored the first book, held the first conference, and wrote the first magazine column on data warehousing. He currently focuses on developing the revolutionary technology known as textual ETL.

No pipelines needed. Stream data with Pub/Sub direct to BigQuery

Pub/Sub’s ingestion of data into BigQuery can be critical to making your latest business data immediately available for analysis. Until today, you had to create intermediate Dataflow jobs before your data could be ingested into BigQuery with the proper schema. While Dataflow pipelines (including ones built with Dataflow Templates) get the job done well, sometimes they can be more than what is needed for use cases that simply require raw data with no transformation to be exported to BigQuery.