If you’re one of the many Data Studio users writing custom queries for BigQuery, you can now run parameterized queries. This provides better customization and interaction options to your users while making your reports faster.

When connecting to BigQuery from Data Studio you can use special date parameters or define your own named parameters as part of a custom query. Parameters in custom queries introduce two key benefits: queries can be dynamically updated from the report - no need to create new data sources; this works even if the report user does not have edit access to the data source. You can optimize query cost and gain dashboard performance improvements since less data is passed from BigQuery to Data Studio for parameterized queries.

Creating parameterized custom queries

To allow report editors to choose which corpus to analyze from Shakespeare’s works you can use the Custom Query interface of the BigQuery connector in Data Studio to define corpus as a parameter as part of a filter. You can define the type of UI element for the parameter (e.g., text input, single select, checkbox, etc.) and provide default values.

In the following example, the corpus parameter has been defined as a single-select dropdown with Hamlet as the default value along with other works as options such as Othello, King Lear, etc.

What’s really cool is that once you’ve defined the configuration, report editors will then be able to choose a specific corpus to analyze by using the dropdown from the parameters section of the report property panel:

Using date parameters

Prior to date parameters, custom queries for date sharded or partitioned tables could not be limited to a date range based on a report’s date control. Instead, your custom query would have to fetch all rows for all dates, leaving Data Studio to do the job of filtering for the date range selected by the report user. The result is slower and less efficient reports.

With date parameters, you can use the reserved start and end date parameters as part of a custom query. When report users select a date range for analysis the dates selected will automatically be included as part of your custom query, resulting in a much more efficient query and fetching only the rows needed for the requested date range.

The following example custom query uses the @DS_START_DATE and @DS_END_DATE parameters as part of a filter on the creation date column of a table. The records produced by the query will be limited to the date range selected by the report user, reducing the number of records returned and resulting in a faster query:

The standard Data Studio date settings and controls will determine the date values for your custom query. A report editor can set a default date or add a date control to a report and the start and end dates for your query will change based on the report date control.

In both cases, named and date parameters offer a more efficient way to retrieve data from a single BigQuery data source while giving your report users flexible options to analyze different data.

Try it out!

To learn more about how parameters work review data source parameters and connecting to BigQuery. 

As you have a chance to experiment with parameters, send us feedback or give us a shout out at @googleanalytics.

Data Studio, Google’s data visualization platform, includes a developer features that expand the flexibility and functionality of your dashboards. Using Data Studio community connectors and community visualizations, you can connect to any internet-connected data source, and create custom visualizations tailored to your data and storytelling needs.

Recently, we created the Data Studio Community Component generator (dscc-gen), a command-line tool that streamlines building community connectors and community visualizations. dscc-gen provides working templates and opinionated workflows that make it quick and easy to create and deploy your projects.

Community Connectors tooling

Typically, developing a community connector means using the online Apps Scripts environment. The online editor is an excellent tool that can be used for all online tasks, but it doesn't support automating repetitive (and error-prone) tasks. By using a project generated from dscc-gen, updating a deployment becomes as easy as running npm run update_production and trying out your latest changes is just npm run open_latest.

To create a new community connector with dscc-gen, just run this command:

npx @google/dscc-gen connector

After the command finishes, you will have a working connector with a production deployment and best-practice deployment scripts. If you have an existing connector, you can still use dscc-gen to get the best-practice deployment scripts. See existing connectors for details.

For more information on commands that are available, see the local development developer documentation.  

Community Visualization tooling

Typically, developing a community visualization means editing local files, re-uploading the changes, and reloading a Data Studio report. This template provides a local development cycle and scripts that make bundling and deploying your code a breeze. By using a project generated by dscc-gen, deploying a visualization with caching enabled becomes as easy as running npm run build:prod && npm run push:prod.

To create a new community visualization with dscc-gen, just run this command:

npx @google/dscc-gen viz

After the command finishes, you will have a working visualization with a lightning-fast local workflow and best-practice build/deployment scripts.

For a rundown of how to best use this tool, visit the local development developer documentation.

Templates and use casesOur tooling supports the most common use-cases for connectors and visualizations. We’ve open sourced the library and code on GitHub, where you can make and request improvements.

Looking forward

Community Visualizations as Chart Filters

At the beginning of 2019, we introduced richer interactivity in Data Studio, enabling charts to  act as filters, facilitating more interactive data explorations and faster time to insight. If you’ve been following the community visualizations developer preview, you may have noticed that community visualizations haven’t yet supported chart interaction filters.

Now, we’ve added the capability for developers to add filter interaction functionality to community visualizations. When interacting with a community visualization that supports filter interactions, your interactions with the community visualization can filter the rest of your dashboard.

For example: below is a community visualization heatmap that acts as a chart interaction filter.

Community visualizations acting as chart filters make even more custom, interactive charts possible in your reports. You can create calendar heatmaps where you can click-and-drag to select a date range, or a timeseries chart where you filter dragging a rolling window along your chart. You could even create a dendrogram of organizational chart data, and select different nodes to filter the dashboard by the individuals represented at each node.

Report editors can enable filter interactions for each visualization, and use them to filter other components on the dashboard, just like the Data Studio built-in charts.

We’re continuing to add features to make community visualizations more powerful and easier to use. Learn how to add filter interactions to your community visualization by reviewing our developer documentation, and sign up to keep up with the latest in Data Studio developer features.

To start 2019, the Data Studio team added a number of new features to allow for faster insights and richer reporting. Today, we’ll highlight some of these recent launches.

Interactive Charts

We’re extending Data Studio’s filtering capabilities directly into our charts. Editors can now turn any chart into a filter that filters other charts. When viewing a dashboard, you can now click or brush on any data in order to initiate filters, enabling much faster exploration and shortening the time to insight.

Search Filters

See the help center article here to learn more.

Embed External Content

We’re making it easy to bring in any content from the web to your report. Now, you can embed an entire webpage in a Data Studio report. You can add YouTube videos explaining your content, Google Sheets containing the source data for your report, Forms to get feedback on the usefulness of your report, or any embeddable content from the web.

As always, we will continue to introduce new features and enhancements based on your feedback. Please request features and upvote your favorites here.

Data Studio provides a variety of easy-to-use charts to help you tell stories with your data, allowing you to visualize data from different sources. Sometimes, though, you want a custom chart to convey information more effectively to your teams, or to customize style options for the kind of data you are presenting.

The new Data Studio Community Visualizations feature, in developer preview, allows you to build new charts and styling options, providing even more freedom and flexibility in the stories you tell with your data. Community visualizations integrate seamlessly with the rest of your Data Studio dashboard, including all of the data sources you bring together, to enable you to quickly gain insight from your data.

What are Community Visualizations?

Community visualizations integrate seamlessly into your dashboards. You can use them with all of your data sources, and configure the data and styling options in the property panel, just like you would with a built-in chart.

ClickInsight, a Google Marketing Platform partner, says this about community visualizations:

"Choosing the right chart type is essential to effectively telling a story with data. Thanks to Community Visualizations, we now have the flexibility to build our own charts to suit every unique situation."

Developer preview launch

The Community Visualizations developer preview launch means that the Community Visualization feature is stable and enabled for all users. To build a community visualization, you should be comfortable with JavaScript, HTML, and writing visualization code. However, there are many features and improvements you can look forward to in the coming year.

To learn more about Community Visualizations and how to get started, visit Community Visualizations, Developer Preview. Once you’ve built a visualization you’d like to share, submit a report to the showcase and share your code with other Data Studio users.

It's been a busy year for Data Studio Community Connectors. Since the developer launch, we've added over ten new features, had significant growth, seen partners grow their businesses, and collaborated with the community on open source projects. As we move forward, we're reflecting on what has been accomplished, and what's coming next for Community Connectors.

Where were we last year?

In late 2017, we launched Community Connectorsto allow Data Studio users to connect to their external data and started working with partners to bring access to new data sources. The developer preview provided a platform for developers to build connectors, but there were a lot of features to add and work to do before it was ready for a full launch. This is what we've been busy working on the last year. Since then, we've seen 140+ partner connectors, 500+ data sources, integrated solutions, and fun data sets.

Now that we've delivered on the key improvements and updates highlighted at the outset of the developer launch, we've concluding the developer preview phase. Let's look at what's been added in 2018.

New Developer Features

Throughout 2018, we‘ve added features to improve the connector developer experience and enabled new use-cases.

We introduced the community-connectors GitHub repository as a place to let the community contribute open source connector code.

There are new ways to authenticate a connector. Services that expect username & password, API tokens, or username and API key are easier to add. See Authentication for full details.

Connectors can define the semantic types for their schemas ahead of time. This means your users no longer have to tweak settings on the schema configuration page every time they make a data source from your connector.

The Data Studio Apps Scripts service is now available and provides useful builders & validation to make building a connector a breeze.

Some other features worth mentioning:

• Direct links to a connector can pre-populate the config

• Links provided in the manifest description and info config entries are now clickable

• Connectors can force viewers credentials for data sources created from the connector

• Configuration entries can be parameterized so they can be changed without creating a new data source

• Schema fields can be hidden

What Partners Are Saying

Our connector partners and their customers have seen great success with community connectors. Mikael Thuneberg, CEO of Supermetrics, had this to say:

"The focus we’ve put on creating high-quality connectors has been rewarded by the large number of companies around the world who have chosen these as their primary cross-platform marketing reporting tool. [ … ] Data Studio connectors have become an exciting and rapidly growing business area for Supermetrics."

Marc Soares, Manager at Clickinsight, has also seen success through community connectors:

"[Community Connectors have] allowed us to fully take advantage of Data Studio as a central reporting platform. Thanks to community connectors, our analysts spend less time making reports and more time conducting meaningful analysis for our clients."

What's Coming Next?

Next year, we're planning to provide even more ways to configure connectors, extending existing features, and adding more educational content to help you get the most out of community connectors.

If you're new and want to get started making your own connector, check out the codelab and  documentation. To stay up to date with changes and the community, see support for options.

It’s been a great year, and we're excited for what's coming in the future.

As of today, Kaggle is now officially integrated with Data Studio, Google’s serverless business intelligence and data visualization platform. You’ll be able to connect to and visualize Kaggle datasets directly from Data Studio using the Kaggle Community Connector.

Kaggle is the world's largest online community of data scientists. Its two million users come to the platform to explore, create, and share data projects using Kernels, a free hosted notebook IDE. Over 10,000 public datasets can be analyzed using Kernels, accessed via the web or Kaggle's public API. This new integration, users can analyze these datasets in Kaggle; and then visualize findings and publish their data stories using Data Studio.

Here’s an example dashboard in Data Studio using a Kaggle dataset:

As a free-to-use reporting solution, Data Studio makes it easier for users to understand their data, derive key insights, and effectively communicate findings using compelling interactive dashboards. Data Studio is creating an innovative landscape where users can spend less time building their data pipeline and more time on creating data stories and sharing them with the right audience.

With this integration, users can browse to a dataset in Kaggle, pick a file, and use the one-click integration button to launch Data Studio with the selected data. From there, users can create and publish their own interactive dashboard, which can be embedded in websites and blogs. Since there is no cost to use Data Studio and the infrastructure is handled by Google, users don't have to worry about scalability, even if millions of people view the dashboard.

Here’s a quick clip showing how easy it is to use this integration to build dashboards in Data Studio:

See Connecting Kaggle Datasets to Data Studio to learn more.

Data Studio helps data professionals bring the power of visual analytics to their data. The hassle-free publishing process means everyone can tell engaging stories, open up dashboards for others to interact with, and make better-informed decisions. We're also releasing the connector code for this integration in the Data Studio Open Source Repository. This should help both Data Studio developers and Kaggle users to build newer and better solutions.

To get started, try out a Kaggle maintained dataset and launch the Kaggle connector for Data Studio. Let’s analyze more data and build awesome dashboards!