What’s New With Google Cloud for 2022

As organizations rapidly accelerate their digital transformations to meet industry needs, it’s important to have a cloud data platform foundation that enables them to stay ahead of the curve. In 2021, Google Cloud Platform continued its dedication to enabling partners, customers, and practitioners alike to achieve their data-driven goals by offering new solutions, features, and updates to existing tools.

Pandera is empowered through Google Cloud to provide top-tier solutions across the data and analytics landscape. The market is ever-changing, and thanks to Google Cloud’s dedication to providing new updates and features for their products and services, Pandera is able to better assist organizations with their data-driven goals. As we begin the next chapter, here’s a look at what’s new with Google Cloud for 2022.

Vertex AI

Launched in May of 2021 in general availability, Vertex AI broadens the horizons for artificial intelligence (AI) and machine learning (ML) on Google Cloud Platform. Specifically, this new solution enables organizations to accelerate the deployment and maintenance of AI models.

Vertex AI requires nearly 80% fewer lines of code to train a model versus competitive platforms, empowering data scientists and engineers to build reliable, standardized AI pipelines that take advantage of the power of Google Cloud’s data pipelines

Additionally, Vertex AI Workbench was launched in preview during Google Cloud Next 2021. This service allows for a unified user experience to build and deploy ML models faster, accelerating time-to-value for data scientists and organizations.

Vertex AI Workbench also features integrations across data services (like Dataproc, BigQuery, Dataplex, and Looker), which significantly reduce context switching.

BigQuery Omni

General availability for BigQuery Omni, a multi-cloud analytics service, was announced at Google Cloud Next 2021. This solution assists data and analytics teams to break down barriers by using BigQuery to securely and cost-effectively analyze data across clouds.

BigQuery Omni is now available to all customers on Amazon Web Services and for select customers on Microsoft Azure. The solution enables secure connections to S3 data in AWS or Azure Blob Storage data in Azure.

BigQuery itself also received two features tailored toward better administration via the BigQuery Administrator Hub, Resource Charts, and Slot Estimator.

Google Cloud and Looker

Google Cloud announced updates for Looker in July of 2021 to help organizations deliver data-driven experiences at scale. The first exciting new looker feature is the Extension Framework available as part of the new Looker Developer Portal. The framework allows developers to build applications and data experiences easier by letting it handle hosting, authentication, authorization, and more.

In addition, Looker 21 also gained additional upgrades, such as:

API Explorer – an interactive way to explore the Looker API, prototype requests, and execute complex API calls without writing code.
Filter components – allows developers to bring the filters they declare on any dashboard in Looker into any embedded application or extension.
Cloud Cost Management solution – offers out-of-box robust reporting and BI capabilities to get up and running quickly with transparency across the three major clouds.
Looker mobile app – allows everyone to get insights on the go on their mobile devices. The app is available in 22 languages and supports biometric authentication like face or touch ID.

With Looker’s mission to empower people through the smarter use of data, these features enable organizations to build rich data-driven experiences for all.

Google Distributed Cloud

Also announced at Google Cloud Next ‘21 was Google Distributed Cloud. This is a portfolio of fully managed hardware and software solutions built on Anthos.

With businesses seeking accelerated cloud adoption for various benefits, some of their workloads cannot move to the public cloud entirely or right away, due to multiple factors. These factors range from compliance and data sovereignty needs, low latency or local data-processing requirements, or because they need to run close to other services.

That’s where Google Distributed Cloud comes in, which extends Google Cloud’s infrastructure into customers’ data centers and out to the edge of the network.