Solving for the next era of innovation and efficiency with data and AI
Even in today’s changing business climate, Google customers’ needs have never been more clear: They want to reduce operating costs, boost revenue, and transform customer experiences. Today, at Google third annual Google Data Cloud & AI Summit, Google are announcing new product innovations and partner offerings that can optimize price-performance, help you take advantage of open ecosystems, securely set data standards, and bring the magic of AI and ML to existing data, while embracing a vibrant partner ecosystem. Our key innovations will enable customers to:
- Improve data cost predictability using BigQuery editions
- Break free from legacy databases with AlloyDB Omni
- Unify trusted metrics across the organization with Looker Modeler
- Extend AI & ML insights to BigQuery and other third-party platforms
Help reduce operating costs for BigQuery
In the face of fast-changing market conditions, organizations need smarter systems that provide the required efficiency and flexibility to adapt. That is why today, we’re excited to introduce new BigQuery pricing editions along with innovations for autoscaling and a new compressed storage billing model.
BigQuery editions provide more choice and flexibility for you to select the right feature set for various workload requirements. You can mix and match among Standard, Enterprise, and Enterprise Plus editions to achieve the preferred price-performance by workload.
BigQuery editions include the ability for single or multi-year commitments at lower prices for predictable workloads and new autoscaling that supports unpredictable workloads by providing the option to pay only for the compute capacity you use. And unlike alternative VM-based solutions that charge for a full warehouse with a pre-provisioned, fixed capacity, BigQuery harnesses the power of a serverless architecture to provision additional capacity in granular increments to help you not overpay for underutilized capacity. Additionally, Google are offering a new compressed storage billing model for BigQuery editions customers, which can reduce costs depending on the type of data stored.
Break free from legacy databases with AlloyDB
For many organizations, reducing costs means migrating from expensive legacy databases. But sometimes, they can’t move as fast as they want, because their workloads are restricted to on-premises data centers due to regulatory or data sovereignty requirements, or they’re running their application at the edge. Many customers need a path to support in-place modernization with AlloyDB, our high performance, PostgreSQL-compatible database, as a stepping stone to the cloud.
Today, Google are excited to announce the technology preview of AlloyDB Omni, a downloadable edition of AlloyDB designed to run on-premises, at the edge, across clouds, or even on developer laptops. AlloyDB Omni offers the AlloyDB benefits you’ve come to love, including high performance, PostgreSQL compatibility, and Google Cloud support, all at a fraction of the cost of legacy databases. In our performance tests, AlloyDB Omni is more than 2x faster than standard PostgreSQL for transactional workloads, and delivers up to 100x faster analytical queries than standard PostgreSQL.
And to make it easy for you to take advantage of our open data cloud, we’re announcing Google Cloud’s new Database Migration Assessment (DMA) tool, as part of the Database Migration Program. This new tool provides easy-to-understand reports that demonstrate the effort required to move to one of our PostgreSQL databases — whether it’s AlloyDB or Cloud SQL. Contact us today at g.co/cloud/migrate-today to get started with your migration journey.
Securely set data standards
Data-driven organizations need to know they can trust the data in their business intelligence (BI) tools. Today we are announcing Looker Modeler, which allows you to define metrics about your business using Looker’s innovative semantic modeling layer. Looker Modeler is the single source of truth for your metrics, which you can share with the BI tools of your choice, such as PowerBI, Tableau, and ThoughtSpot, or Google solutions like Connected Sheets and Looker Studio, providing users with quality data to make informed decisions.
In addition to Looker Modeler, we are also announcing BigQuery data clean rooms, to help organizations to share and match datasets across companies while respecting user privacy. In Q3, you should be able to use BigQuery data clean rooms to share data and collaborate on analysis with trusted partners, all while preserving privacy protections. One common use case for marketers could be combining ads campaign data with your first-party data to unlock insights and improve campaigns.
Google are also extending our vision for data clean rooms with several new partnerships. Habu will integrate with BigQuery to support privacy safe data orchestration and their data clean room service. LiveRamp on Google Cloud will enable privacy-centric data collaboration and identity resolution right within BigQuery to help drive more effective data partnerships. Lytics is a customer data platform built on BigQuery, to help activate insights across marketing channels.
Bring ML to your data
BigQuery ML, which empowers data analysts to use machine learning through existing SQL tools and skills, saw over 200% year overview growth in usage in 2022. Since BigQuery ML became generally available in 2019, customers have run hundreds of millions of prediction and training queries. Google Cloud provides infrastructure for developers to work with data, AI, and ML, including Vertex AI, Cloud Tensor Processing Units (TPUs), and the latest GPUs from Nvidia. To bring ML closer to your data, we are announcing new capabilities in BigQuery that will allow users to import models such as PyTorch, host remote models on Vertex AI, and run pre-trained models from Vertex AI.
Building on our open ecosystem for AI development, Google are also announcing partnerships to bring more choice and capabilities for customers to turn their data into insights from AI and ML, including new integrations between:
- DataRobot and BigQuery provide users with repeatable code patterns to help developers modernize deployment and experiment with ML models more quickly.
- Neo4j and BigQuery, allowing users to extend SQL analysis with graph data science and ML using BigQuery, Vertex AI and Colab notebooks.
- ThoughtSpot and multiple Google Cloud services — BigQuery, Looker, and Connected Sheets — which will provide more AI-driven, natural language search capabilities to help users more quickly get insights from their business data.
Accelerate your Data Cloud with an open ecosystem
Over 900 software partners power their applications using Google’s Data Cloud. Partners have extended Google Cloud’s open ecosystem by introducing new ways for customers to accelerate their data journeys. Here are a few updates from our data cloud partners:
- Crux Informatics is making more than 1,000 new datasets available on Analytics Hub, with plans to increase to over 2,000 datasets later this year.
- Starburst is deepening its integration with BigQuery and Dataplex so that customers can bring analytics to their data no matter where it resides, including data lakes, multi and hybrid cloud sources.
- Collibra introduced new features across BigQuery, Dataplex, Cloud Storage, and AlloyDB to help customers gain a deeper understanding of their business with trusted data.
- Informatica launched a cloud-native, AI-powered master data management service on Google Cloud to make it easier for customers to connect data across the enterprise for a contextual 360-degree view and insights in BigQuery.
- Google Cloud Ready for AlloyDB is a new program that recognizes partner solutions that have met stringent integration requirements with AlloyDB. Thirty partners have already achieved the Cloud Ready – AlloyDB designation, including Collibra, Confluent, Datadog, Microstrategy, and Striim.