We believe everyone should be able to use data to make decisions. The Data Explorer makes the power and flexibility of our analytics API more accessible. Now that the Explorer is open source, developers can embed it anywhere — making it easier to build analytics tools for your teams or add value for your customers by incorporating white-labeled analytics directly within your product.

What can I do with the Data Explorer?

The Data Explorer interacts directly with event data stored in Keen IO. It’s an extremely simple and intuitive query interface built to explore event data. All of the analysis functions are built in. Even better, your teams and your customers do not need to know complex query language like SQL to run their analysis. Here’s how you might use the open source Data Explorer:

Empower your teams — Quickly empower teams with a tool to easily answer their own questions with data

— Quickly empower teams with a tool to easily answer their own questions with data Improve your product — If you’re a SaaS company using Keen to power customer-facing dashboards, you can give your customers another tool to explore the data that matters to them.

— If you’re a SaaS company using Keen to power customer-facing dashboards, you can give your customers another tool to explore the data that matters to them. Build something new — Build a completely new analytics product — Want to build an analytics panel just for product managers? Or your own version of Google Analytics? Data Explorer lowers the barrier for you to do so.

Key features

The Explorer has all the functionality of an analysis tool built in and ready to go. Your teams and customers can intuitively build queries, create charts, and extract data within seconds.

Query building

Choose your collection — signups, downloads, pageviews — whatever collection of data you need

— signups, downloads, pageviews — whatever collection of data you need Choose your analysis type — count, count unique, sum, min, max, average, select unique, percentile, median

— count, count unique, sum, min, max, average, select unique, percentile, median Ask deep questions by running a group by on any property

by running a group by on any property Build a filter for your query, using the event type as a base for your filter — choose from string, number, null, list, Boolean, or date/time

for your query, using the event type as a base for your filter — choose from string, number, null, list, Boolean, or date/time Try out the geo-filter , which enables you to to filter events by latitude/longitude

, which enables you to to filter events by latitude/longitude Pick a date and time range for your query using our calendar selector

Visualize the results

Toggle between different visualizations of your data, choosing from chart types including area, line, table, or pie. You can also view your results in a metric or JSON format.

of your data, choosing from chart types including area, line, table, or pie. You can also view your results in a metric or JSON format. Embed the charts anywhere by viewing the source code and pasting it anywhere

by viewing the source code and pasting it anywhere Save your favorite queries , so you can come back and access them again and again

, so you can come back and access them again and again Extract your events — view the raw data by sending a full extraction to your email

Why now?

We built Keen IO to solve the increasingly difficult challenge of event data collection, storage, and analysis at scale. We aim to make it easy to not only analyze data via API, but also to expose data to your teams and customers who need it.

Our first couple years at Keen, we focused primarily on building the analytics API and backend tools. While that remains our top priority, we now have a team of engineers focused on building out our front-end and visualization offerings, and Explorer is one of our open source product releases. We’re excited about growing this team to better serve your needs.

We’re so grateful for all of the feedback we’ve received from our developer community along the way. If you have any feedback or questions, please send us an email or ping us on Slack!

Ready to explore your own data? Request a demo, check out the sample demo or fork the project on Github.

Happy Exploring!