As organizations continue to produce vast quantities of data, they increasingly need platforms that allow them to analyze, store, and extract meaningful insights from that data. And research from analyst firms like Gartner offer an important way for organizations to evaluate and compare cloud data warehouse providers.

Earlier this year, Gartner named Google a Leader in the 2019 Gartner Magic Quadrant for Data Management Solutions for Analytics (DMSA) (report available here). This evaluation covers Google Cloud’s core data analytics offerings, including BigQuery, a serverless, managed data warehouse, Cloud Dataproc, a managed Spark and Hadoop service, and Cloud Dataflow, which enables you to stream and batch-process your data. Here are a few takeaways:

Simplicity and speed

BigQuery’s performance permits complex queries on large-scale data sets to return in seconds, and a substantial number of BigQuery customers maintain data warehouses that store more than 50 terabytes (and a few customers now use more than 100 petabytes). More than half of these customers are loading data either continuously or many times per day. These customers value the ability to extract, transform, load, and analyze their data on a serverless platform, all without maintaining any underlying infrastructure.

A versatile serverless data warehouse

One of BigQuery’s major advantages is its ability to allow customers to address a wide variety of use cases—from a traditional data warehouse to data science. Over the past year, we’ve worked hard to introduce new features in BigQuery like data types for financial and monetary uses, BigQuery GIS for geospatial data, and machine learning capabilities through BigQuery ML. BigQuery’s continuous ingest capabilities make it suitable for an operational—or a real-time—serverless data warehouse.

An expanding ecosystem

With overall increased market adoption, our analytics offerings continue to benefit from a fast-growing partner ecosystem of service providers, and business intelligence (BI) and data integration vendors. In particular, in 2018 we expanded our partnerships with established industry providers, including Confluent, Dell Boomi, Informatica, Looker, Reltio, Tableau, and ThoughtSpot.

More and more organizations are finding value in Google Cloud’s serverless data warehouse and analytics offerings. If you’d like to learn more, you can download a complimentary copy of the Gartner Magic Quadrant for Data Management Solutions for Analytics on the Google site (requires an email address).

_{Gartner does not endorse any vendor, product or service depicted in its research publications, and does not advise technology users to select only those vendors with the highest ratings or other designation. Gartner research publications consist of the opinions of Gartner’s research organization and should not be construed as statements of fact. Gartner disclaims all warranties, expressed or implied, with respect to this research, including any warranties of merchantability or fitness for a particular purpose.}

Want to know the latest from Google Cloud? Find it here in one handy location. Check back regularly for our newest updates, announcements, resources, events, learning opportunities, and more. 

Tip: Not sure where to find what you’re looking for on the Google Cloud blog? Start here: Google Cloud blog 101: Full list of topics, links, and resources.

Week of May 24-May 28 2021

• Google Cloud for financial services: driving your transformation cloud journey–As we welcome the industry to our Financial Services Summit, we’re sharing more on how Google Cloud accelerates a financial organization’s digital transformation through app and infrastructure modernization, data democratization, people connections, and trusted transactions. Read more or watch the summit on demand.
• Introducing Datashare solution for financial services–We announced the general availability of Datashare for financial services, a new Google Cloud solution that brings together the entire capital markets ecosystem—data publishers and data consumers—to exchange market data securely and easily. Read more.
• Announcing Datastream in Preview–Datastream, a serverless change data capture (CDC) and replication service, allows enterprises to synchronize data across heterogeneous databases, storage systems, and applications reliably and with minimal latency to support real-time analytics, database replication, and event-driven architectures. Read more.
• Introducing Dataplex: An intelligent data fabric for analytics at scale–Dataplex provides a way to centrally manage, monitor, and govern your data across data lakes, data warehouses and data marts, and make this data securely accessible to a variety of analytics and data science tools. Read more. 
• Announcing Dataflow Prime–Available in Preview in Q3 2021, Dataflow Prime is a new platform based on a serverless, no-ops, auto-tuning architecture built to bring unparalleled resource utilization and radical operational simplicity to big data processing. Dataflow Prime builds on Dataflow and brings new user benefits with innovations in resource utilization and distributed diagnostics. The new capabilities in Dataflow significantly reduce the time spent on infrastructure sizing and tuning tasks, as well as time spent diagnosing data freshness problems. Read more.
• Secure and scalable sharing for data and analytics with Analytics Hub–With Analytics Hub, available in Preview in Q3, organizations get a rich data ecosystem by publishing and subscribing to analytics-ready datasets; control and monitoring over how their data is being used; a self-service way to access valuable and trusted data assets; and an easy way to monetize their data assets without the overhead of building and managing the infrastructure. Read more.
• Cloud Spanner trims entry cost by 90%–Coming soon to Preview, granular instance sizing in Spanner lets organizations run workloads at as low as 1/10th the cost of regular instances, equating to approximately $65/month. Read more.
• Cloud Bigtable lifts SLA and adds new security features for regulated industries–Bigtable instances with a multi-cluster routing policy across 3 or more regions are now covered by a 99.999% monthly uptime percentage under the new SLA. In addition, new Data Access audit logs can help determine whether sensitive customer information has been accessed in the event of a security incident, and if so, when, and by whom. Read more.
• Build a no-code journaling app–In honor of Mental Health Awareness Month, Google Cloud’s no-code application development platform, AppSheet, demonstrates how you can build a journaling app complete with titles, time stamps, mood entries, and more. Learn how with this blog and video here.
• New features in Security Command Center—On May 24th, Security Command Center Premium launched the general availability of granular access controls at project- and folder-level and Center for Internet Security (CIS) 1.1 benchmarks for Google Cloud Platform Foundation. These new capabilities enable organizations to improve their security posture and efficiently manage risk for their Google Cloud environment. Learn more.
• Simplified API operations with AI–Google Cloud’s API management platform Apigee applies Google’s industry leading ML and AI to your API metadata. Understand how it works with anomaly detection here.
• This week: Data Cloud and Financial Services Summits–Our Google Cloud Summit series begins this week with the Data Cloud Summit on Wednesday May 26 (Global). At this half-day event, you’ll learn how leading companies like PayPal, Workday, Equifax, and many others are driving competitive differentiation using Google Cloud technologies to build their data clouds and transform data into value that drives innovation. The following day, Thursday May 27 (Global & EMEA) at the Financial Services Summit, discover how Google Cloud is helping financial institutions such as PayPal, Global Payments, HSBC, Credit Suisse, AXA Switzerland and more unlock new possibilities and accelerate business through innovation. Read more and explore the entire summit series.
• Announcing the Google for Games Developer Summit 2021 on July 12th-13th–With a surge of new gamers and an increase in time spent playing games in the last year, it’s more important than ever for game developers to delight and engage players. To help developers with this opportunity, the games teams at Google are back to announce the return of the Google for Games Developer Summit 2021 on July 12th-13th. Hear from experts across Google about new game solutions they’re building to make it easier for you to continue creating great games, connecting with players and scaling your business. Registration is free and open to all game developers. Register for the free online event at g.co/gamedevsummit to get more details in the coming weeks. We can’t wait to share our latest innovations with the developer community. Learn more.

🎧 Prefer to listen? Check out this episode on the Google Cloud Reader podcast

If you’re anything like me, you love reading, but also appreciate that sometimes your eyes need to be doing other things; whether it’s finding your exit off the highway, or keeping your puppy from destroying the couch.

And sometimes the thought of sitting down to read something just feels like it’s going to take valuable multi-tasking time away from my day. I know, I know, multitasking can be frowned upon, but it’s the way I live a good chunk of my life, and it’s working out so far. And while I’m not alone in my multitasking, I’m also not alone in my desire for a non-visual way to get this content, or any content.

*Google Cloud Reader enters the chat*

Google Cloud Reader is a podcast that lets you listen to the Google Cloud Blog posts that aren’t as dependent on visuals. This means they’re articles that are, or are adapted to be, less focused on graphs, or code samples, and instead describe the meaning behind those visual aids. 

It’s an easy, audible way to absorb content around all things new in Cloud, while still being able to make sure Ruthie doesn’t eat my work from home equipment. 

So by now you’re probably thinking “OK, so you started a podcast during the pandemic, even though you definitely seemed like the type to start making sourdough”—and you’re right. My 53 plants agree with you. But rest assured, one can listen to an episode of this podcast *while* creating a macramé plant hanger, or waiting for bread to rise—multitasking, am I right?

We’re a little over 50 episodes/macrame plant hangers in, so you should check it out (Ruth and I would appreciate it).

Some of my personal favorites 

• Beginners Guide to Painless Machine Learning – Learn how to get started with Google Cloud AI tools
• Introducing GKE Autopilot: A Revolution in Managed Kubernetes – Learn more about GKE Autopilot, a revolutionary mode of operations for managed Kubernetes that lets you focus on your software, while GKE Autopilot manages the infrastructure.
• Cook up your own ML recipes with AI Platform – ​​Learn about Mars Wrigley’s new ML-inspired recipe experiment on Google Cloud and how you can get started with your own.
• Recovering Global Wildlife Populations using ML – Review Google’s Wildlife Insight’s ML project and help users create an image classification model for motion-sensor cameras (called camera traps) used to help protect wildlife in an non-invasive way by collecting and tagging species via pictures.

Let me know your favorite episodes, and what other articles you’d like to hear on Twitter @jbrojbrojbro!

No matter why you prefer an audio format, we’ve got you covered; Google Cloud Reader, where we read the tech blog for you, and to you.

Get all the Google Cloud Reader on your favorite podcast platform, including Google Podcasts, Apple Podcasts, and Spotify.

Data-savvy businesses increasingly rely on images and videos for critical functions, and yet are challenged by the sheer mass of information—more than 3.2 billion images and 720,000 hours of video are created daily. This explosion in visual data has paved the way for the growth of computer vision, a form of artificial intelligence (AI) that enables computers to “see” the world similarly to the way people do, but with unblinking consistency, and greater accuracy. 

The transformational impact and value of computer vision solutions are significant and has been a guiding objective for companies and AI developers. And yet, even as the applications for computer vision increase dramatically, architecting and implementing vision AI solutions remain highly complex. Visual data, such as images and video, are made up of thousands of pixels of information that represent millions of different patterns and meanings, which can make interpreting even a single image overwhelming from a computational perspective.

Many organizations struggle with deployments and fail to operationalize vision AI solutions due to development delays, machine learning and data science hiring challenges, inaccurate output, a lack of integration with existing infrastructure, difficulty of use, and high cost. Plainsight, with the power of Google Cloud resources, is addressing all these challenges and helping businesses by enabling the deployment of vision AI within enterprise private networks that can be managed easily and scaled economically.

Plainsight has announced availability of its vision AI platform on Google Cloud Marketplace. Businesses can now easily deploy end-to-end vision AI to private clouds to realize the full value of their video and other visual data for accurate, actionable insights across diverse use cases.

Delivering on the Promise of AI: Seeing What’s Hiding In Plain Sight

For organizations to integrate AI and machine learning into their businesses successfully, the technology must be powerful enough to solve real challenges, yet fast, easy, and accessible enough to ensure the innovation potential is realized. Plainsight on Google Cloud delivers the power of enterprise vision AI that’s quick and easy to use with Google Cloud resources that enable global scale, increased security, bolstered privacy, unified billing, and cost savings. 

To streamline vision AI workflows, Plainsight facilitates the entire pipeline, from visual data ingestion and annotation, through continuous model training, deployment, and monitoring for easier innovation and faster time-to-production. Our platform accelerates vision AI development in a manner that is complete, accurate, and accessible to non-technical business leaders. We believe that AI should be available and accessible to anyone and everyone—so that teams across entire organizations can reap the benefits. 

By integrating Plainsight into their private networks, companies worldwide can now leverage one intuitive platform for centralized control of streamlined vision AI model creation and training with optimized visual data handling for diverse enterprise solutions. These use cases include: social distancing monitoring, medical imaging, drug compound screening, defect detection in manufacturing processes, identifying gas leaks, or even livestock counting and crop health monitoring for agriculture, to name a few.https://www.youtube.com/embed/A7U_0UkjvEg?enablejsapi=1&

We enable customers so they can create successful solutions that enable them to clearly see their business from all angles and to take advantage of the knowledge visual data can reveal by simply and quickly operationalizing practical vision AI applications.

AI-Powered Dataset Creation, Automated Model Training & Easy Deployment Without A Single Line Of Code 

For vision AI applications, success is inextricably dependent on the quality and quantity of the datasets required to train the relevant models. To aid enterprises in this vital stage, the Plainsight platform provides built-in data annotation for the fast and easy creation of datasets. This includes AI-powered features that accelerate the speed and quality of labeling such as SmartPoly, for the automated polygon masking of objects, TrackForward, to predict and automatically label objects from frame to frame in video annotations, and AutoLabel for automated object recognition and labeling based on pre-trained machine learning models, to highlight a few.

In addition, to ensure the success of AI integration, we significantly reduce time-intensive processes with Plainsight vision AI’s automated machine learning with continuous model training and easy deployment capabilities. In just a few clicks, users can leverage optimizations for the most reliable model training without endless experimentation cycles. And, models are easily deployed at scale all within one, easy-to-manage model operationalization process for the business.

Growing With Google Cloud

Plainsight is a vision AI innovation leader, developing solutions that address unmet needs for challenger brands and Fortune 500s across vertical markets. As a team recognized for succeeding where others have failed, our expanding partnership with Google Cloud provides a powerful combination that helps customers see and activate the value of their visual data with a suite of services in a secure and private manner.

Our vision AI Platform simplifies building and operationalizing AI to solve business problems enterprises are facing every day—and the demand is increasing. To accelerate our journey to faster, more accessible AI for enterprises, we knew we needed strong support to grow Plainsight and scale our backend tools to match our vision. 

Google Cloud delivered everything, and more, in one program. The Startup Program by Google Cloud provided the technology and services for scale and the support we needed to maximize the value the Program provided us. The Startup Program has been a springboard for architecting Plainsight vision AI in the cloud, accelerating our goals and optimizing innovation, efficiency, and growth. The team also helped us optimize Google Ads campaigns, fueling adoption of Plainsight. 

After launching the SaaS version of Plainsight Data Annotation in November 2020, we grew our user base by nearly 110x in just three short months. Google Ads has also dramatically increased website traffic, growing new users by nearly 5.75X and page views by over 5X. The Google team helped us identify where Google Cloud offerings could be leveraged instead of developing in-house solutions and offered best practices that enabled us to deliver faster on our initiatives. 

Kubernetes was already the underlying component of our platform and leveraging Google Kubernetes Engine (GKE) as a managed service removed a layer of complexity. By combining GKE and Anthos, we were able to standardize our deployments, aligning to how our customers leverage Anthos for enterprise applications in their own organizations. In addition, as a fast-moving, customer-centric company we use Google Workspace to help us centralize and manage our day-to-day work internally. By leveraging multiple products across Google’s ecosystem, we take advantage of a holistic partnership that has helped our business tremendously as we scale. 

Leveraging Google’s Partners for Strategic Consultation

To facilitate this expansion of our partnership with Google and to maximize our use of Google Cloud services, we are working with DoiT International, a Google Managed Services Provider and 2020 Global Reseller Partner of the Year. DoiT provides us with ongoing technical consultation for cloud-native architecture, Google Cloud Marketplace integration, production-grade Kubernetes support, Google Cloud cost optimization, and technical support. The DoiT team has been invaluable in compiling best practices, tips, and strategies from their vast experience with various cloud customers to ease our Marketplace integration and is providing input for infrastructure strategy to support our continued rapid growth.

Plainsight Delivers Enterprise Vision AI Through The Google Cloud Platform Marketplace

Plainsight vision AI is now available to Google Cloud Customers on Google Cloud Marketplace enabling organizations across industries to deploy private Plainsight instances within their own environments. Marketplace customers will benefit from Google Cloud privacy, security, scalability and unified billing through their Google Cloud account. 

Combining the powerful benefits provided by Google Cloud resources with Plainsight’s vision AI Platform into private networks, enterprises worldwide can now leverage one intuitive platform for centralized control of streamlined vision AI model creation and training with optimized visual data handling for diverse enterprise solutions. 

Through our Google partnership, we’re able to leverage a powerful foundation that allows us to rapidly innovate, scale and accelerate delivery on our vision AI platform capabilities. By executing on our vision to make AI easier, faster and more accessible for all users across entire enterprises, we’re helping businesses see more and by seeing more, they’ll have the power to solve more. 

If you want to learn more about how Google Cloud can help your startup, visit our page here where you can apply for our Startup Program, and sign up for our monthly startup newsletter to get a peek at our community activities, digital events, special offers, and more.