In March 2016, Google unveiled Data Studio 360, a new data visualization platform for enterprises as part of Google Analytics 360 Suite. A free version, Google Data Studio, was announced a few months later at Google Performance Summit in May 2016. Initially, a limited free version was only available in the US. Google Data Studio later became free for everyone without report limitation and “globally available” to more countries in March 2017. Although rumored to become Generally Available sometime in Q1 2017, the product is still in beta.
Google Data Studio Overview
Google Data Studio is a free collaborative data visualization product, tightly integrated with other components of the Google portfolio including: Google Analytics 360 Suite, DoubleClick Campaign Manager, Google AdWords, Google BigQuery, YouTube, Google Sheets and more. The product leverages Google Cloud Storage (GCS), Google account/authentication and Google Docs functionalities, offering advanced built-in security/authentication and sharing capabilities.
It is available in 37 languages and in most countries, Russia being the most recent country added in August 2017. The list of unsupported countries to date can be found here along with the supported languages.
Like all modern data visualization offerings, Google Data Studio lets users:
- connect to data,
- create custom calculations, dashboards and reports,
- share and collaborate with others.
The sign up and getting started process is fast and free, allowing users to be functional in a few minutes.
We put Google Data Studio to the test to better understand the key strengths and areas of improvement of the product. Let’s review what we found out.
- Price (free)
The data visualization market is a mature, commoditized and crowded market. Low-priced SaaS Business Intelligence offerings are the new norm and Google being a major cloud player, Data Studio is no exception.
While low-priced/giveaway cloud software does not tell the whole story, as explained in a recent InformationWeek article, Google Data platforms or applications customers with simple data visualization needs may find the product compelling.
- Integration with Google portfolio
Google Data Studio is tightly integrated with the Google Cloud portfolio from direct query to Google Cloud data sources, Google Analytics 360 Suite, DoubleClick Campaign Manager, Google AdWords, Google BigQuery, YouTube, Google Sheets and more.
- Full Cloud
Compared to some competitive cloud solutions, Google Data Studio is a full cloud offering that does not rely on any Desktop for data modeling or authoring. This simplifies the architecture and the workflow for users, avoiding version control issues and allowing faster time to insight/collaboration.
- Starter Kits
The templates and gallery of sample reports offered out of the box – although limited today – allow users to easily get started. By adding their own data source to a copy of a sample report, users can have a nice, fully functioning report in minutes.
- Built-in authentication and collaboration capabilities
Google Data Studio leverages Google account/authentication, Google Groups and Google Docs functionalities, offering strong authentication and sharing capabilities, including real time collaboration like in Google Docs.
Main Areas for Improvements
More than 15 months after its initial announcement, Google Data Studio is not a GA product yet.
As per the terms of service: ”Any use of Beta Features will be solely at your own risk and may be subject to additional requirements as specified by Google. Google is not obligated to provide support for Beta Features, and Google may cease providing Beta Features as part of the Service”.
- Data connectivity
Despite some recent improvements with the launch of a community with third party connectors in the September 6th release, the range of data sources Google Data Studio can connect to out of the box is promising but still limited, compared to competitive products. Excel users need to upload Xls files to Google Sheets or saved them first in CVS UTF-8 format.
- Limited data storage
Google Data Studio leverages Google Cloud Storage (GCS) which only offers 2 GB total free storage per user and has a 100 MB file size limit per data set, which is lower than what most competitive products offer. For example, Microsoft Power BI offers 10 GB per user with the freemium version and has a 1GB file size limitation (but no sharing). AWS QuickSight free tier has a 1GB data storage and file size limits, but again note this comes with no sharing capabilities.
Update 9/25/2017: Per William Vambenepe, Google Group Product Manager, free tiers are product-specific offerings of free usage for new or existing customers, and they never expire. Google BigQuery has two free tiers: one for storage (10GB) and one for analysis 1TB/month. To prevent exceeding these limits, it is wise to monitor usage with Google Stackdriver charts and alerts; furthermore, users can put spending limits on their accounts.
- No hybrid data architecture
While competitive products can access on-premises data sources from the cloud either via direct query or via sync mechanisms, Google Data Studio needs on-premises data to be manually uploaded to the cloud. In addition, there is a limit of 100 uploads per data set per day and no scheduled, incremental refresh. Uploaded data is appended to existing data, not merged with it, making it quite easy for novice users to have duplicate records.
- Data preparation, transformation and blending
Google Data Studio has basic data preparation capabilities compared to competitive products: nothing automatic or wizard based, only through formulas. Example: no ability to split a field into multiple fields in a few clicks.
The product provides a good list of functions, which should be enough for most users with basic needs but limited compared to competitive products. Example: no calculation of aggregated values cumulatively in a partition (running total, etc.)
Most importantly, Google Data Studio does not have data blending capabilities. Reports can use multiple data sources, but individual charts and controls must be based on a single data source, forcing users to prepare and consolidate their data outside of the product. This is reportedly on the roadmap and expected to be delivered in a near future. Well…this has been expected for a while, as a matter of fact a sneak peek of what the data blending interface could look like was “leaked” 6 months ago, but this still remains one of the top requests on the user community website.
Update 9/25/2017: Per William Vambenepe, Google Group Product Manager, Google Data Studio is often used in conjunction with Google Cloud Data Prep that recently went into a public beta status as of September 21 which can save to Google BigQuery or Google Cloud Services.
- Limited breadth of usage
Google Data Studio is a simple data visualization product. While the range of visualizations offered is good, it is inferior to competitive products and cannot be extended.
Data discovery capabilities are weak, the interactivity is very limited: no click anywhere, no drill, no search on data (only via predefined filters), no global filtering, no filter across data sources and so on.
Despite incremental improvements, other capabilities commonly found in competitive products like export to PDF, alerting, storytelling are still missing in the product.
Overall, Google Data Studio has a limited breadth of usage beyond simple data visualization: no pixel perfect reporting, no advanced analytics, no innovative augmented analytics capabilities (augmented insight, Natural Language Generation and Processing) …yet.
While Google is releasing new versions of Google Data Studio quite regularly and has a strong roadmap, the product has still a long way to go to catch up with competitive products. Today, Google Data Studio is a nascent product, not an enterprise solution that can be deployed broadly within organizations. The product targets individuals and small businesses, its sweet spot being users/customers who have simple data visualization needs on top of Google data. It is not a strong enough data visualization layer that can help Google sell cloud data platforms and services yet.
However, “augmented analytics” with the automation of insights using machine learning and natural language generation is, per Gartner “the next wave of market disruption” (See the Augmented analytics is the future of Data and Analytics in this Gartner Report or this summary from Gartner Analyst Rita Sallam). While modern BI and analytics platforms are adding augmented analytics capabilities to feature rich and increasingly hard to differentiate solutions, Google has definitively a card to play in this market.
Google Cloud is a force to be reckoned with and the market leader when it comes to machine learning based on the series of announcements made during their annual Google Cloud Next 2017 user conference in March 2017. Also notable, Google was the only leader in The Forrester Wave™: Insight PaaS 2017.
That wraps up our quick review of Google Data Studio. We will continue to monitor Google’s progress and will keep you posted. If you want to explore the product, check out the following resources.