Search driven analytics is a new way how you can make ad-hoc queries and get answers simply by entering search query. This works like Google search but for your own dataset, and instead of list of links you get reports with numbers. Search driven analytics is especially good when you need to enable data-driven decisions in your company by non-IT staff - they don't need to know anything about pivot tables and visualization, as reports are configured automatically by search.
SeekTable Ask a question function allows you to perform data exploration with simple search queries. Just enter free-form natural language query and get answers in the form of pivot table or chart. SeekTable helps to form the question with keywords auto-completion: suggestions come from the dataset itself and the cube configuration.
Everyone can use search-driven analytics and get the results for data-driven decision making. Try these online demos:
average television by age range and gender
show sales sum in 2011 vs 2012 by region and month
Sometimes you can get something different from what you expect; in this case you may back to your search query by returing to cube dashboard ("back" in a web browser or click on the cube name in the breadcrumbs) and add more keywords.
Currently natural language queries are supported only for CSV data sources; we'll enable it for databases a bit later.
sum of total. To use first "Sum" measure it is enough to specify just
closed(may refer to 'state' or 'status' column).
name John. Hint is required if you want to filter by high-cardinality column (when engine cannot determine a dimension by specified word or phrase).
2019 Mar. Note that these 'partial' dates are applied correctly only when your cube has separate dimensions for date parts (year, month, day).