Google BigQuery is a serverless, highly scalable, low-cost enterprise data warehouse that helps data analysts become more productive. It enables extremely fast analytics on a petabyte scale. And its pay-as-you-go model makes it attractive for organizations looking to move away from a CAPEX-based model for data warehousing. In response to the growing interest in BigQuery, Pythian’s Google Cloud Platform Qualified Solutions Developers and Cloud Data Engineers have put together a white paper that guides you through the process of evaluating whether BigQuery is a good fit for your use case, then takes you, step-by-step, through a migration from Teradata to BigQuery.
The authors of this white paper are some of Pythian’s Google Cloud Platform qualified experts who help enterprises around the world get the most from their Google Cloud Platform implementations, including BigQuery. For example, they recently implemented BigQuery as part of a solution that transformed the way the England and Wales Cricket Board (ECB) understands and reaches their thousands of participants and fans. With BigQuery, their ability to perform analytics has resulted in increased ticket sales, improved venues for matches, improved player selection, youth team engagement and more. Read the full story.
In Pythian’s latest white paper, A Framework for Migrating Your Data Warehouse to Google BigQuery, Pythian experts provide all of the information you need to migrate from Teradata to BigQuery with confidence. It guides you through all aspects of the migration, from initial considerations to step-by-step instructions with examples that cover the pre-migration, migration and post-migration process.
Get the white paper now
Download the Framework for Migrating Your Data Warehouse to Google BigQuery white paper to learn about:
- When it makes sense to migrate to BigQuery, and when it doesn’t
- The key areas to consider when planning for and implementing a migration of this nature
- Pre-migration considerations like how to approach cost control tools, data transformations and continuous data ingestion
- Step-by-step instructions on how to set up a data migration pipeline from Teradata to BigQuery
- Post-migration procedures like how to monitor your BigQuery database using Stackdriver, analyzing logs and validating data quality