Looker Studio has introduced enhancements for better data visualization and user experience. It now offers data preview in the data source editor for Google BigQuery, Google Sheets, Looker, Microsoft Excel, and CSV uploads. A new security feature provides redirect notices for external links. Updates include improved funnel charts and scorecard charts, along with better field management options and enhanced metadata protection.
Google Cloud has enhanced its Visual Studio Code extension with BigQuery support in preview, allowing developers to work with BigQuery datasets and notebooks directly in VS Code. New features include creating and executing BigQuery notebooks using Python kernels and managing datasets by browsing and previewing them. Developers can access these features through the Google Cloud Code section in VS Code and must install the bigframes client library.
Google has updated Looker Studio with enhanced filtering and connector features for better data analysis. New date and time filtering options include conditions for specific periods, cutoff dates, and current or upcoming timeframes. The Looker connector now offers an advanced filter for more precise data control. Additionally, Google has renamed some fields in the Search Ads 360 connector to resolve naming conflicts, while keeping the original functionality intact.
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Google has updated BigQuery, allowing Analytics Hub publishers to monetize their data offerings via Google Cloud Marketplace. This integration facilitates scalable data sharing. Publishers can list data products, manage specifications, pricing models, and subscription durations. Subscribers benefit from a broader selection of data products, but face limitations, such as standard Analytics Hub restrictions and no support for data clean rooms.
Looker Studio has introduced updates including automated chart titling that generates titles based on chart type and fields, with customization options. The New Search Ads 360 connector now offers additional visualization fields. New educational resources are available through Cloud Skills Boost Labs for training on Looker Studio. A Conversational Analytics guide powered by Gemini allows users to analyze data through conversational interactions.
Google has launched generative AI models Veo and Imagen 3 on Vertex AI. Veo enables companies to create high-quality videos from text or images, streamlining production. Imagen 3, available next week, generates realistic images from text prompts and offers editing features. Both models prioritize safety with digital watermarking and filters. Businesses like Mondelez and Agoda are using these tools to enhance content creation and marketing.
BigQuery has announced a significant enhancement to its search indexing capabilities, now supporting `INT64` and `TIMESTAMP` data types in search index creation. This feature has reached general availability (GA) status. The complete list of supported data types now includes STRING, INT64, TIMESTAMP, ARRAY<PRIMITIVE_DATA_TYPE>, STRUCT (with supported nested fields), and JSON (with supported nested fields).
Google announced that Gemini integration in BigQuery will transition from free to paid access, ending the free period on January 27, 2025. Users must choose between BigQuery Enterprise Plus edition reservations or a Gemini Code Assist Enterprise license. Compliance considerations include differing security features from standard BigQuery. Organizations can restrict Gemini access. This change marks Google's move to monetize AI integration.
Google BigQuery has introduced new AI-powered SQL translation capabilities using the Gemini model. Features include customizable GoogleSQL translations, translation rule creation, migration-specific adjustments, location-specific support, and rule-based translation modifications. Preview features offer AI-powered translation suggestions, Gemini model integration, configuration YAML file support, automated batch processing, and enhanced accuracy.
