Debug, change your mind, and validate.
Take an existing dataset or a create a new one that represents customer behavior.
Inspect a few example customers or dive into why a metric is lower than expected.
Change your mind, add more features, or create more aggretations easily.
Stakeholders want to see data sliced by an infinite list of features. For each new slice, you don't have to worry about joining in new columns. Narrator handles the added SQL complexity for you.
"Only show customers who opened an email within 30 minutes of getting a call, but ignore production emails"
"Hmm, I want to see the same exact data for the Started Checkout activity instead of the Completed Order activity"
"A session is attributed to linear advertising only if it occured during a spike of more than 60 sessions in 5 minutes."
Data is never perfect. When exploring we need to be able to dive into any row and see where that row came from. Instead of 50 SELECT * where action is X queries, just right click. Same goes for any aggregation or metric. Right click and get all thew raw data that makes up that data point.
"What did a person buy before coming back to the website?"
"Which ad source are our most frequent customers coming from?"
"Wait, did 100 people really sign up last week?"
"Who came from this specific ad source?"
"Give me the 500 people who converted last holiday season so I can prepare a re-engage campaign."
"Give me everyone who hasn't logged in in the last 2 weeks so I can proactively reach out to them."
SQL isn't great at handling changes or downstream effects. Dataset solves that problem by being flexible and simple to use. We worked with hundreds of analysts to create a UX that follows your thinking patterns.
Never duplicate a SQL query to edit.
Never worry if your CTE changes.
Keep all the slices you have created in one clean interface.
See the company or activity events, automatically on plots so you don't debug something you know already.
Filters have auto-complete and tables have summaries so you are always informed.