At Next’22, Google Cloud laid down the welcome mat to an array of big data software providers, enabling them to become first-class citizens in its cloud.
The company also announced a slew of upgrades to its own wares, including its distributed analytics database BigQuery, while also unifying its analytics tools under the Looker brand and launching a new AI Agent.
Google may be the king of search, but many folks like Elastic Search, which has gained a substantial following over the past decade. The integration unveiled at Next’22 will see Google Cloud users able to federate search queries to their data lakes using Elastic Search. Meanwhile, Google added Looker support to the Elastic platform, enabling users to embed search insights into their Looker apps.
The partnership with MongoDB will offer new templates to improve customers’ ability to move data between Atlas, MongoDB’s hosted database service, and BigQuery. Google Cloud sees this as a path to enabling its Vertex AI capabilities to be used by MongoDB customers.
Collibra, which develops data catalogue and governance products, is being integrated with Google Cloud’s data fabric offering, dubbed Dataplex. The integration will bolster joint customers’ ability to discover data, understand data lineage, and apply consistent controls on data stored across cloud and on-prem environments, the company says.
Palantir, the big data software provider for law enforcement, also announced that it would start using BigQuery as its data engine for Foundry Ontology, which the vendor refers to as the operational layer for its platform. The combination will connect “underlying data models to business objects such as plants, distribution centres, or equipment, enabling customers to more effectively manage and understand data from their most critical assets,” Google Cloud asys.
Google Cloud Rises
Google Cloud also made several enhancements to its big data analytics software offerings, including analysing unstructured and streaming data in BigQuery.
The capability to analyse unstructured data in BigQuery will undoubtedly meet the approval of users who work with a lot of text and image data. These folks gain the ability to access Google’s machine learning, speech recognition, computer vision, translation, and text processing capabilities directly from BigQuery’s SQL interface, the vendor says.
Google Cloud is also turning BigQuery into a place to bring streaming and historical data together. It’s doing this by launching Datastream for BigQuery, which will replicate data from AlloyDB, PostgreSQL, MySQL, and Oracle databases directly into BigQuery, thereby giving BigQuery users access to the latest data.
Google Cloud is known to tout the openness of its offerings. That reputation was bolstered with today’s announcement that BigQuery now supports Apache Iceberg. This open-source table format solves many challenges associated with using the Apache Hive metastore format. What’s more, Google Cloud has committed to supporting the other two main open table formats, including Delta Lake, developed by Databricks and sponsored by the Linux Foundation, and Apache Hudi.
There’s also some Apache Spark-related news coming out of Next. Google Cloud announced the preview of a new integration between Spark and BigQuery “that allows data practitioners to create BigQuery stored procedures using Spark that integrate with their SQL pipelines,” the company says. Google Cloud has also unveiled Vertex AI Vision, which the company bills as an end-to-end environment for building and deploying computer vision apps.
Looker for All
On the business intelligence front, Google Cloud announced that it’s putting all its BI, core AI, and machine learning tools under the Looker umbrella. Looker and Data Studio, a Google Cloud tool introduced back in 2016, will now be called Looker Studio. Three versions of Looker Studio will be available. There will also be Looker Studio Pro, which adds support and governance.
“With this complete enterprise business intelligence suite, we will help you go beyond dashboards and infuse your workflows and applications with the intelligence needed to help make data-driven decisions,” Kate Wright, Google Cloud’s senior director of BI product management, writes in a blog post.
AI Agents
Finally, Google Cloud also unveiled a slew of new AI agents that it says will help accelerate the adoption of AI in organisations.
“While investments in pure data science continue to be essential for many, widespread adoption of AI increasingly involves a category of applications and services that we call AI Agents,” June Yang, Google Cloud’s vice president of cloud AI and industry solutions, writes in a blog post today. “These are technologies that let customers apply the best of AI to common business challenges, with the limited technical expertise required by employees.”
Google Cloud already offers two AI Agents. Those include Document AI, which functions as an AI assistant to help with the handling and processing of documents, and Contact Center AI. This chatbot can route customers and analyse call centre transcripts. Google Cloud launched one more AI Agent today. Translation Hub, as it’s called, provides self-service document translation among 135 languages.
