Unlock insights with ease: Data Studio and Cloud Dataprep are now generally available

We build products at Google Cloud to make life easier for our customers—to enable them to organize, access, and understand their world of information. Although different businesses have different needs, virtually all of them want a comprehensive view of their data. But that can mean managing purpose-built IT infrastructure, or spending large amounts of time cleaning up messy data before it can ever be put to use.

Today, we’re excited to announce the general availability of both Google Data Studio, our free modern business intelligence product, and Cloud Dataprep, our fully-managed data preparation product, powered by Trifacta.

Data Studio

When we launched Data Studio in 2016, we set out to build a simple-to-use but powerful business intelligence (BI) platform to make visual analytics more accessible. With Data Studio, you can easily access and analyze data from Google Cloud and Google Marketing Platform sources alongside more than 500 other data sources via more than 100 partner-built connectors. This means you can visualize and interactively explore data in compelling dashboards or reports, easily share insights with others or collaborate in real-time with colleagues, whether you’re sitting across the room or across continents. As a result, it’s now being used by over a million people around the world, every single month.

During our two years in which we’ve run a fruitful public beta, we’ve carefully listened to our customers and expanded critical capabilities of Data Studio. Users in retail, financial services and insurance, marketing, technology, hospitality, media, and other verticals inspire us with their questions and examples around supply-chain, marketing, sales analytics, and data storytelling use cases. We’re also especially inspired by the data stories being generated though our Visualize 2030 contest, grounded in the United Nations’ 2030 Agenda for Sustainable Development.  

A few experiences from our customers

AirAsia Group (AirAsia) operates flights across Asia and beyond. Founded in 2001 as a pioneer of low cost air travel in southeast asia, AirAsia has grown to serve more than 222 routes and 110 destinations from hubs in Malaysia, Thailand, Indonesia, the Philippines, and India.

"Data Studio helps to keep AirAsia data flowing through the organization,” says Nikunj Shanti, Chief Data Officer, AirAsia. “Data democratization is the key for future efficiencies within the airline and the integration between Data Studio and BigQuery data sources help ensure that everyone has a single view. The platform has rapidly evolved in the last 12 months, and we’re able to sunset existing production and ensure we have a single platform for data dashboard and ad-hoc visualization."

Based in the UK, Ocado is the world’s largest online-only grocery retailer, and it offers the Ocado Smart Platform sales and logistics system to third-party retailers.

“Data and analytics are crucial to not only the success of Ocado's retail business and Ocado Smart Platform, but also to our Software Engineering teams,” says Dan Nelson, Head of Platform Services, Ocado. “Having standardized on GCP, we've expanded our BI stack to take advantage of the close integrations of Data Studio and BigQuery, with a heavy focus on system reliability and engineering cycle times. Due to the cost and high skill barriers to entry of our existing tools, teams in the past would manually create one-off dashboards and spreadsheets on static data. With Data Studio we've quickly brought our system health and productivity metrics into our data ecosystem and exposed, with secure access, performance data dashboards. Now all teams have their own ad-hoc, real-time view of the data specific to not only their systems and processes, but the entire development unit. Brilliant.”

PicMonkey empowers users to create stunning photos, logos, social media graphics, and Facebook covers with PicMonkey’s easy yet powerful photo editing and graphic design software.

“We used to try to create artificial situations to figure out which digital experiences perform best, but that’s not very real-world,” says Karen Cooper, Brand Director, PicMonkey. “With BigQuery and Data Studio, we can very quickly see which combinations are most successful. That’s been a tremendous improvement in developing a consumer-facing product.”

Continuous investments in Data Studio

Data Studio beta users have influenced the product’s evolution and inspired our vision for its future. We recently introduced Data Studio Explorer, an ad-hoc data exploration component of Data Studio. Its native integration within BigQuery’s UI gives our users the ability to turn their datasets and query results into a visualization, literally in a few clicks.  

Blending data from disparate sources in a single chart is also now as simple as a right-click inside Data Studio.

In addition to popular Google Cloud data sources like BigQuery, Sheets, Cloud SQL, Cloud Spanner and Cloud Storage, Data Studio works with popular Google advertising and marketing data sources  like Google Analytics, Display & Video 360, YouTube Analytics, and Google Ads. Further, organizations can gain access to over 500 data sources like Salesforce, Facebook, Twitter, and more, through our community connectors partner ecosystem. A custom report template gallery makes getting started fast, with filter-like controls for the data source you’re interested in. And in just a few weeks, we will launch a new community feature to support custom visualizations, allowing you to build your own visualizations for Data Studio using 3rd party libraries like D3.js or custom JavaScript and CSS.

We hope you recognize that the team is just getting started with Data Studio! We’ll continue to release new features and additional enhancements to the product. In the meantime, you can get started by visiting datastudio.google.com, connecting to your data sources, and exploring our template gallery. As always, feel free to ask us questions and send us feature requests. Data Studio is your product as much as it is ours.

Cloud Dataprep

Data processing techniques and tools may have evolved, but one headache in data processing has remained constant: bad input data with anomalies, gaps, and inconsistencies. Taking action on bad data often leads to bad results, but cleaning and preparing data typically requires a lot of time and coding from developers and subject matter experts.

We believe data preparation is important and allows you to unlock the full potential of cloud data analytics tools like BigQuery and Google Cloud Dataflow. We introduced Google Cloud Dataprep to make data preparation easy, fast, and powerful through an intuitive and serverless visual interface, As of today, it is generally available.

We’re launching the general availability of Cloud Dataprep with a number of new features frequently requested by our user community. These new features make it easier to do the core tasks involved in data preparation: exploring, cleaning, and enriching data.

• A new look: The landing page for Cloud Dataprep has been updated to show recent activity, and new users will get up-to-speed quickly with an improved onboarding experience.
  
• Team-based data preparation: Teams can now collaborate on data preparation by sharing flows, collaborate on recipes in real-time, re-using samples, and reviewing an audit trail to see who did what and when.
  
• Powerful features for business analysts: Business analysts can be more productive with Google Sheets-like pivots and unions, improved source:target schema matching, and parameter-based dataset processing.
  

On any given day, Cloud Dataprep has organizations scheduling thousands of predefined jobs or performing ad-hoc data preparation. Customers like Foundation for Precision Medicine, Alpha Vertex, Unacast, Craveable Brands, and Farmlogix are taking advantage of Cloud Dataprep to make it easier and faster to work with their data.  

“At Farmlogix, we’re making data accessible for the sustainable food industry,” says Linda Mallers, President & CEO, Farmlogix. “Because reporting is an integral part of our business, we called on Google Cloud to help transfer our data into an environment that was better suited for our needs. Cloud Dataprep by Trifacta is incredibly user-friendly. The machine learning suggestions help us reduce a big chunk of the labor-intensive process of data wrangling, so we can analyze and mine food purchasing data across 46 states, 521 distributors, and 1,000 producer groups representing over 100,000 farms and vendors. That’s how we’re able to reimagine local and sustainable sourcing and regional supply chains.”

You can easily get started exploring, cleaning, and enriching your data by following one of our how-to guides. Since Cloud Dataprep is serverless, if you’re an existing user, all of these new features are immediately available and existing jobs do not require modification. For more information, you can always review the Cloud Dataprep release notes and use the google-cloud-dataprep tag on Stack Overflow for questions.

Looking ahead, with insight

When combined with BigQuery, our fully-managed and easy-to-use enterprise data warehouse, Data Studio and Cloud Dataprep comprise key components of Google Cloud’s business intelligence and marketing analytics solutions. Keep an eye on this space as we continue building out features and enhancements, based on your experiences and feedback. In the meantime, ready your data for analysis and machine learning with Cloud Dataprep or start exploring and visualizing all your critical data with Data Studio.