Below you can find all analytics-focused queries currently supported by SlicingDice.
Know how many unique entities you have in a particular dimension satisfy the query conditions.
Check documentation for count entities queries.
Know the number of times some data was inserted for event columns in a particular dimension.
Check documentation for count events queries.
Generate insights from the data stored at SlicingDice by calculating metrics and crossing data from different columns to generate pivot tables.
Check documentation for aggregations queries.
Know what are the most common values for a specific column and how many times was the value inserted into it.
Check documentation for top values queries.
Check whether the given entity IDs exist in a dimension.
Check documentation for exists queries.
Know how many unique entities you have in a particular set of dimensions (or in the whole database).
Check documentation for total queries.
Differently from analytics-focused queries, data extraction methods allow you to retrieve data stored on SlicingDice. Below you can find all data extraction queries currently supported by SlicingDice.
Allows you to retrieve data from columns you have stored.
Check documentation for result queries.
Allows you to retrieve data while receiving the entities' relative importance given a set of conditions.
Check documentation for score queries.
Please note that API responses may be paginated to speed up data retrieval from SlicingDice. Check the pagination documentation to learn how to handle pagination on SlicingDice.
Remember that there is no cost for you to use test databases to make data insertions and queries before inserting real data to your production database.
All SlicingDice's clients/SDK have many ready-to-use examples on their Github repositories.
Check the our client/SDK page to know more.