# Explores Overview ## Data models Whether working in Daasity app or your company's Looker enviornment, you'll begin your data exploration in one of the available data models (e.g. Explores). **Daasity provides a set of analytical reporting models with unified data, as well as source-specific data models for many integrations.** 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](/core-concepts/data-integrations/setup-guides.md) and your [Brand Supplied Data](broken://pages/oHvwJ3b4pFzgnjSSOYnb) into [Unified Schemas](/core-concepts/data-models/unified-schemas.md) and [Data Marts](/core-concepts/data-models/unified-schemas/data-marts.md), on top of which we build our analytical data models. {% hint style="success" %} Some[ Integrations Populate an Explore](https://help.daasity.com/visualization/explores/integration-explores) used to build custom reports {% endhint %} [Click Here to Learn How to Access your Explores](/core-concepts/bi-tools/looker/working-with-explores/how-to-access-an-explore.md) ## 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.* ### I**dentify the Subject Area** **For Example, within Digital Analytics there are** * [Inventory](/core-concepts/data-models/data-explores/digital-analytics-unified/ecommerce-inventory-explore.md) * [Customer Details](/core-concepts/data-models/data-explores/digital-analytics-unified/customer-details-explore.md) * [Orders](/core-concepts/data-models/data-explores/digital-analytics-unified/ecommerce-orders-and-revenue-by-order-date-explore.md) * [Traffic](/core-concepts/data-models/data-explores/digital-analytics-unified/traffic-explore.md) * [Returns](/core-concepts/data-models/data-explores/source-specific/loop-returns-explore.md) * [Subscribers](/core-concepts/data-models/data-explores/source-specific/subscription-explores.md) * [Shipping](broken://pages/h0BG0ZZczEoXHVNUXogH) ## 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 --- # Agent Instructions: Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. 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