Google Cloud Computing announced a number of important upgrades to the Data Cloud platform, with a focus on strengthening the openness and intelligent governance capabilities of the data lake architecture. This update includes native support for the Apache Iceberg open format, and integration of enterprise-level cloud computing storage through BigLake services, combined with artificial intelligence automated data governance, for enterprises and development teams to improve elasticity and efficiency in data management, analysis and application. Wukong plays gold clothes, and brushes monsters to collect the Five Elements Orb! Ad 9377 Legendary Wukong plays gold clothes, and brushes monsters to collect the Five Elements Orb! This update features BigLake’s native support for Apache Iceberg, combining Iceberg’s open-format data management capabilities with Google Cloud Storage. Enterprises can efficiently analyze Iceberg datasets through BigLake Table, and apply mechanisms such as Google Cloud Survival Integral Layer Management and User-Owned Encryption Keys. Through BigLake Metastore’s new API and REST Catalog, developers can more easily integrate multi-source Iceberg data, and support collaboration with BigQuery, AlloyDB for PostgreSQL, and third-party analysis engines to reduce ETL costs and improve cross-platform data access elasticity. Google also launched an automated relocation tool to assist enterprises in quickly relocating existing data environments such as Hadoop or Delta Lake to Iceberg. The upgrade of the data lake architecture not only enhances the analysis layer, but also extends to the operation database and artificial intelligence application integration. BigQuery now supports high-end applications such as real-time query, data reorganization and multi-table transaction of Iceberg data. Enterprises can use BigQuery in streaming media processing, machine learning and multi-modal analysis scenarios while maintaining data autonomy. AlloyDB for PostgreSQL can also directly query Iceberg data managed by BigLake, supporting semantic search and natural language query, enabling the operation and analysis data layers to be more closely connected, reducing the trouble of data replication and transformation. The Dataplex Universal Catalog is also one of the focuses of this update. The service integrates relay data from different sources such as BigLake, BigQuery, Spanner, and Vertex AI to achieve unified exploration, organization, and governance. Combined with the Gemini AI model, Dataplex can automatically analyze data associations, perform intelligent annotation, semantic search, and analysis suggestions, improve data inventory and governance efficiency, and strengthen the automation of rights control, data security, and regulatory compliance. Dataplex Universal Catalog also supports integration with third-party governance platforms, making it convenient for enterprises to build cross-cloud and multi-system data governance mechanisms. Amazon Cloud Technology Summit, opening in Shanghai on May 29, free registration! Advertising Amazon Cloud Technology Amazon Cloud Technology Summit, opening in Shanghai on May 29, free registration! Google also integrates Gemini in BigQuery Notebook, providing SQL, Python and Apache Spark integrated development experience, through intelligent prompts, automatic generation of PySpark program code and error diagnosis, reducing learning and operation barriers, supporting JupyterLab and VS Code and other development environment extension components, allowing users to quickly connect Google cloud computing data lake open storage and computing resources, accelerating the development to deployment process.
发表回复