GCP – What’s new and what’s next with data analytics

Data is the foundation for modern enterprises and it goes beyond just collecting and storing it. In a world where things are constantly changing, you need to be able to access and analyze data for insights to drive impactful business decisions. Big data is in our DNA: Google has been at the forefront of data-powered innovation for years, with the mission of organizing the world’s information and making it universally accessible and useful. Google was built to process and analyze large data sets, and the same technology that makes this happen is available for all businesses through our smart analytics platform.

If there’s one lesson from this unpredictable year, it’s that we always need to be prepared for anything. Our customers trust us with their data, which is why our vision centers on offering an analytics platform with proven dependability and security for mission-critical workloads. 

At Google Cloud Next ‘20: OnAir this week, you’ll see our vision come to life across three core principles of our analytics platform: open, intelligent and flexible. Let’s take a deep dive into what’s new in data analytics, and what you can explore this week to help move your data strategy forward. 

Open platform that provides choice and portability

We know that you want options when you’re choosing analytics solutions. That includes choice of deployment across hybrid and multi-cloud , choice to leverage open source services (OSS) and the choice to leverage open APIs to ease migration and data access. BigQuery and its ecosystem of data products bring you an open platform, so you get maximum flexibility for managing analytical applications and data-driven solutions. That’s why we recently announced BigQuery Omni, a flexible, multi-cloud analytics solution that lets you analyze data in Google Cloud, AWS and Azure (coming soon) without moving data. Check out Analytics in a Multi-Cloud World with BigQuery Omni session to learn more.

We also welcomed Looker into Google Cloud earlier this year. Looker is a data and analytics platform that runs on Google Cloud or the cloud of your choice, and can take advantage of the benefits of BigQuery. Looker allows data teams to unleash powerful data experiences and go beyond traditional reports and dashboards to deliver modern BI, integrated insights, data-driven workflows, and custom applications. Looker just announced Looker blocks for the complete Google Marketing Platform, and significant upgrades for application builders are now available in the Looker Marketplace. To learn more about these announcements, check out Looker’s Roadmap: 2020 & Beyond session or their post: New Looker feature enhancements for the data-driven workforce.

Finally, we’re also providing a mix of managed services like Dataproc (what’s new in open source data processing) and the ability to use open source languages like Spark and Presto with the BigQuery Storage API, allowing customers to continue using familiar tools across their data in Google Cloud. These are great examples of how we’re continuing to provide an open platform for our customers.

Built-in intelligent services to do more with what you have

Google Cloud’s smart analytics platform provides intelligent services embedded into our tools and processes, so users don’t have to learn new things to take advantage of it. Businesses want to augment current solutions with AI and ML and optimize business outcomes with real-time intelligence. Google Cloud offers industry-leading AI services to improve those decisions and customer experiences.

With BigQuery ML, for example, users can build custom ML models using standard SQL without moving data from the warehouse. We’ve recently added new models, including boosted trees using XGBoost, DNNs using TensorFlow, K-means clustering, matrix factorization, and more. We’re taking it further by leveraging these models to build real-time AI solutions like anomaly detection, pattern recognition, and predictive forecasting that can be used across multiple industries. These detailed and prescriptive design patterns help you build solutions that can find anomalies in log transactions, like with this telco, detect objects in video clips, or predict customer lifetime value (LTV). Demandbase is currently using BigQuery ML and will hone in on their use cases in What’s New in BigQuery ML, Featuring Demandbase.

Flexibility so you can scale at the speed of business

Finally, we build data analytics tools that provide flexibility. We know that our customers span different industries and multiple use cases. For example, flexibility in BigQuery pricing models lets you uniquely mix and match pricing tiers across environments in order to meet demands and have direct control over cost and performance. Over the past year, we’ve announced Flex Slots, short-term analytics capacity bursts for as little as 60 seconds at a time; a 95% discounted BigQuery promotional offer for new customers with Trial Slots; and now, we’re announcing that you can purchase a minimum of 100 slots at a time in increments of 100 slots. This change applies to all commitment types—flex, monthly, and annual. We’ve heard from SMB and digital-native organizations that they wanted this new pricing tier, and it truly democratizes flat-rate pricing across these different segments. Learn more here.

In addition, we’re catering to different customer needs across our portfolio. Data analysts prefer the familiar SQL interface, which they can access in the BigQuery UI, while data scientists prefer notebook environments, made possible using the Storage API and Dataproc Hub, and business analysts prefer an easy-to-consume BI interface like Looker and Tableau. In addition, you can use a familiar spreadsheet interface with Connected Sheets and natural language interface with the new Data QnA service to draw insights out of your data. For any of these interfaces, all the data lives in BigQuery, so you don’t need to worry about data silos or multiple copies of data. This is true democratization of analytics for everyone.

Proven dependability for mission-critical workloads

For all these things to work, you need a dependable platform that offers security, reliability, governance, and compliance for mission-critical applications. That is why we just announced 4 9s of availability for BigQuery—up to 99.99% availability with guaranteed SLAs, providing peace of mind that the platform will be available to handle all of your needs. 

We’re seeing adoption of our platform across retail, media and entertainment, telecommunications, financial services, transportation and more. You can check out sessions from customers including BlackRock, Iron Mountain, Twitter, MLB, Veolia, Verizon Media, Telus, Carto, Refinitiv, Geotab, Bluecore, and Demandbase. 

Tune in and watch all sessions across our 40+ breakout sessions to learn more from Googlers, customers, and partners, and find them all on-demand afterward. To get started with your data-driven transformation, download this HBR report to find out how data-to-value leaders succeed in driving results from their enterprise data strategy.