Building Queries

Building basic data visualizations and queries is, in effect, a simple 2 step process. The process is designed to be fast, intuitive and ultimately riven through a point-and-click experience without active intervention or scripting. As the user makes their selections and changes, the queries run automatically or can be manually executed - each time redrawing the data into the chosen visual as dictated by the drop zones.

  1. Select a data visualization, which will dictate which "drop zones" are visible. Drop Zones tell us what data elements to put where in drawing the visual in the next step.
  2. Place items from your data model in to the appropriate drop zone to drive the way the visual is rendered. This usually requires a selection of hierarchies and measures:
    1. Select hierarchies (columns) of data elements from your data model (like 'product', 'time', 'customer' etc)
      1. Within hierarchies, you can make specific member element selections (like 'Australia' and 'United States')
    2. Select values (measures or metrics) from your data model (like 'sales', 'quantity', ' row count')

These steps can happen in almost any order, and its not unusual for people to select and change as they go along in an ad-hoc manner (aka "ad-hoc data analysis"). In making selections and adjusting drop-zone assignments, users can build a huge variety of different queries and data visualizations without using any advanced logic or functionality.

Basic to Advanced Querying

Once a user has created a basic data visualization, there invariably is a need to add more sophistication to the query or the visual. To accomplish the more advanced demands for queries, visualizations and reports, the Discover tool exposes a huge amount of advanced features and functions that allows the user to "change" the basic query selections described in the section.

  • Click here to see Changing Queries which covers functionality like, slice, dice, drill, filters, sorts, pivots, totals, eliminations, advanced analytic functions.
  • For even more sophistication, see Calculations which covers functionality like adding formulas, logical lists and query parameterization

Running the Query

Usually, queries auto-execute once selections are made. As a query executes it automatically starts populating the visualization with graphical representations of the data selected. In some scenarios the visualization will not materialize until a minimum amount of structural elements have been selected. Queries can be also be set to run manually, and there are other aspects that can govern the way queries run - including caching and meta data.