Google, on the occasion of its third Google Data Cloud & AI Summit, announced on its blog product innovations and partner offers able to: optimize the price/performance ratio; foster the adoption of open ecosystems; securely set data standards; deliver the benefits of AI and ML to existing data, engaging a dynamic ecosystem of partners.
Google innovations in terms of Data Cloud and AI
The main innovations that Google intends to bring in terms of data cloud and AI, will allow customers to:
- improve data cost predictability with BigQuery editions;
- break free from legacy databases with AlloyDB Omni;
- unify trust metrics across the organization with Looker Modeler;
- extend AI and ML insights to BigQuery and other third-party platforms.
Let’s see them in detail.
Improve the predictability of BigQuery operating costs
With a rapidly evolving marketplace, organizations need smarter systems that deliver efficiency and flexibility. For this reason, Google introduced the new pricing editions of BigQuery, as well as some innovations for autoscaling and a new compressed storage billing model.
The new editions of BigQuery allow for greater choice and flexibility, allowing you to select the feature set that best suits the needs of various workloads and to combine Standard, Enterprise and Enterprise Plus editions to obtain the ideal price-performance ratio based on the workload.
The new editions of BigQuery include the ability to take out annual or multi-year subscriptions at lower prices and the new autoscaling feature supports unpredictable workloads, offering the option to pay only for the compute capacity used.
Additionally, BigQuery leverages the power of a serverless architecture to deliver additional capacity in granular increments, as well as a new compressed storage billing model for customers using BigQuery editions.
Break free from legacy databases with AlloyDB
For some, cutting costs means switching expensive legacy databases. But sometimes workloads are locked into on-premises data centers due to regulatory or data sovereignty requirements, or because apps are managed at the edge.
So many customers need a path to support their ongoing modernization with AlloyDB, Google’s PostgreSQL-compatible high-performance database downloadable with AlloyDB Omni.
AlloyDB Omni offers all the benefits of AlloyDB and is found to be twice as fast as standard PostgreSQL.
Set data standards securely
Data driven companies need to be able to trust the data contained in their business intelligence (BI) tools, so Google has devised Looker Modelera metrics hub that can be shared with the BI tools of your choice, such as PowerBI, Tableau, Thoughtspot, Connected Sheets, and Looker Studio.
In addition to Looker Modeler, there is also BigQuery data clean roomto help organizations share and match datasets with each other while respecting user privacy.
Bring the ML into your data
BigQuery ML enables data analysts to leverage machine learning through existing SQL tools and skills. It also reported more than 200% usage growth in 2022.
Last but not least, to bring machine learning closer to enterprise data, Google announced new features in BigQuery, which will allow users to import models like PyTorch, host remote models on Vertex AI, and run pre-trained models from Vertex AI.
As part of our open ecosystem for AI development, the company is announcing new partnerships that will give customers more choice and the ability to transform data into insights through AI and ML, including new integrations between:
- DataRobot and BigQuery, to help developers experiment with ML models faster;
- Neo4j and BigQuery, to allow users to extend SQL analytics with graph-native data science and machine learning.
- ThoughtSpot and several Google Cloud services – BigQuery, LookML and Google Sheets – will provide more AI-driven natural language search capabilities to help users gain insights from their business data faster.
Accelerate Data Cloud with an open ecosystem
Over 900 software partners rely on Google Data Clouds, introducing new data-driven tools for their customers. Some of the updates made by Google’s cloud data partners include:
- Crux Informaticswhich is making more than 1,000 new datasets available on Analytics Hub, with plans to grow to over 2,000 sets by 2023.
- Starburstwhich is strengthening its integration with BigQuery to enable customers to access analytics for their data regardless of where it resides, including in data lakes or on-premises sources.
- Cockroacheswhich has introduced new capabilities in BigQuery, Dataplex, Cloud Storage and AlloyDB to help customers better understand their business with trusted data.
- Informaticawhich launched an AI-powered, cloud-native master data management service on Google Cloud to make it easier to connect data enterprise-wide, delivering contextual 360-degrees and insights into BigQuery.
- Google Cloud Ready per AlloyDBa new program that rewards partner solutions that meet stringent integration requirements with AlloyDB.