Google Data Cloud is a flexible, performant, and secure data platform that has been built to achieve use cases across all industries. The space rapidly evolving, with Google technologies increasing in functionality. Join this session to gain an understanding of the breadth of the Google Data Cloud, and learn how to begin to leveraging it to gain insights and value from your data.

Topics Include:

• Data cloud overview
• Google Cloud Next 2023 updates
• Key platform components
• Reference architectures

One of the first steps of any data project is to source the data. The database ecosystem is vast and can include different velocities and granularities of data, which can make it difficult to wrangle. This session will review basic concepts of data ingestion, with an introduction to Google capabilities related to loading BigQuery.

Topics include:

• Core data ingestion concepts
• Common source types and connection methods
• Data transformation methodologies
• Available GCP tools

Learn how Google BigQuery's compute and storage internals function. By providing an understanding of how BigQuery works, this session aims to give query writers more context on what goes on behind the blue “Run” button in BigQuery Studio.

Topics include:

• Storage and compute internals
• Partitioning and clustering
• Additional processing mechanisms

Google’s BigQuery was one of the pioneering technologies behind the separation of storage and compute, with unique mechanics that evolve based on customer feedback. With insights tailored toward administrators and developers looking to understand how resource allocation functions, this session provides clarity on how the compute and storage allocation and pricing is designed.

Topics include:

• What is a slot, and how are they managed?
• Budgets and quotas
• BigQuery Editions
• Storage mechanics and pricing