Data Models & Quickstarts
Explanation of how to use Daasity Data Models (e.g. Looker Explores) in Daasity App & Looker environments.
Overview: Data models (e.g. Explores)
The Looker Explores you interact with are data models defined in the Daasity semantic layer, bringing in the tables and metrics needed for the analysis. containing Dimensions (fields such as Product Name, Customer Address, etc.) and Measures (calculations such as Dollar Revenue, Net Sales, etc.).
For instance, how to use the Unified Retail Schema (URS) Explore to analyze data across retailers, or the Unified Order Schema (UOS) Explore for DTC orders.
Daasity combines the data from your Integrations and your Brand Supplied Data into Unified Schemas and Data Marts, on top of which we build our analytical data models.
Some Integrations Populate an Explore used to build custom reports
Click Here to Learn How to Access your Explores
How to choose the Correct Explore
Explores are grouped together based on the Subject Area, i.e., Marketing, Customers, Orders, Traffic, and by the type of information contained within them.
Q: Why isn't all the data related to a particular topic housed in the same explore?
A: Not all data is created equal. Some data or sources cannot be joined to others, and some elements would cause issues like duplicate data. To avoid those types of issues, we've separated them for you.
Identify the Subject Area
For Example, within Digital Analytics there are
Tips on Pivoting, Filtering, and Creating Custom Visualizations
Pivoting Data
Pivot dimensions horizontally by hovering over a field and clicking the Pivot data icon
Supports up to 200 pivoted values (default limit: 50 columns for performance)
Sort pivoted columns by clicking column titles; hold Shift for multi-column sorting
Unpivot by clicking the gear icon and selecting Unpivot, or clicking the Pivot data icon again
Requires at least one unpivoted dimension and one measure in your query
Filtering Your Data
Basic filters: Click the filter icon next to any field in the field picker
Advanced filters: Use "matches (advanced)" for complex expressions and pattern matching
Custom filters: Create sophisticated logic using Looker expressions in the Custom Filter option
Row/column limits: Set limits up to 5,000 rows and 200 columns to optimize performance
Filter behavior: Dimension filters restrict raw data; measure filters limit aggregated results
Custom Visualizations
Quick chart selection: Use visualization icons for common types (table, column, bar, line, pie, etc.)
Advanced options: Click the three-dot menu for additional chart types
Customize visualizations: Click Edit to modify axes, colors, data series, and formatting
Table features: Add row/column totals, reorder columns by dragging headers
Performance tip: Keep pivoted columns under 50 for optimal browser performance
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