Data Explorer Guide
Getting Started with the Data Explorer UI
This guide covers:
- Analyze your Data using the Data Explorer
- Doing Drilldowns & Reporting on Your Data
- Embedding Analytics Into Your Product
Analyze Your Data Using the Data Explorer
Step 1: Log into your Keen account, select your Project
Open the “Streams” tab, and select the Event Collection you’d like to check out. In this example we’re looking at the
SendGrid Email Events data collection.
Step 2: Run some basic queries
Open the “Explorer” tab.
count as the “Analysis Type”, select
SendGrid Email Events as your “Collection Name”, and press “Run Query”. You ran a query!
The type of analysis you can do is vast, here’s a link to read up on what those are. Adding an “Interval” will give you a line graph over time, you can “Group By” properties to view results categorically, and you can add “Filters” to refine the scope of your query.
Save Your Query & Make Your First Dashboard
Step 1: Let’s save your first query
Step 2: Add your graph to a dashboard. Select “Create Dashboard”, name your dashboard, and add the query we saved to the first tile. Then click “Save”.
Congratulations! You’ve created your first dashboard!
Now start digging into your data and creating more custom analyses & visualizations.
Doing Drilldowns and Reporting on Your Data
Select_Unique allows you extract many properties from a single field and filter on a specific segment of users based on any number of fields such as campaigns, clicks, and companyID.
Return a list of unique property values for a single “Target Property”, among all events matching given criteria. You can download the results as a .CSV.
Some example uses for this analysis type:
- List all of the email addresses for people who clicked a certain URL
- List all of the users who performed an action
- List all of the email addresses for a specific company
Extraction feature returns full-form event data with all property values. We strongly believe you should always have full access to all of your data, and we aim to make that as simple and painless as possible.
You can do all the things you can do with
Select_Unique, but we will return you with more data.
Returns the number of unique actors that successfully (or unsuccessfully) make it through a series of steps. “Actors” could mean email addresses, campaigns, or any other identifiers that are meaningful to you.
Actors will fall off at each step, to varying degrees, so a funnel analysis reveals where a given flow loses the most users.
For example, a funnel could include these steps:
- Users who
- Made an in-app
- Lastly, you can grab a list of all of the actors in the last step of your funnel, in this case, people who opened an email and clicked a URL.
You can add as many “Filters” as you’d like to make your funnel more targeted.
Here’s an example funnel: