Data & Metrics Guide
Find plain-English guides and technical references for DataHawk metrics, datasets, dashboards, and marketplace use cases.
Use this guide when you need to understand what your DataHawk data means, how a metric is calculated, where a signal appears, or which technical reference to open next. Start with the core concepts, then choose the topic that matches the question you are trying to answer.
Start here
These foundation pages explain how DataHawk organizes data before you move into a specific analysis area.
How DataHawk Sources Your Data
Public vs. private data, account connection requirements, marketplace coverage, and freshness expectations.
DataHawk Data Concepts
Core identifiers, marketplace concepts, Amazon Vendor views, and Walmart equivalents used across DataHawk.
Choose a topic
For analysts and developers
The pages above explain the business meaning and methodology. When you need schemas, table families, grains, joins, SQL examples, or field-level references, use Technical Reference.
Help Center
This space is designed to help you quickly find the answers you need, whether you're getting started or going deeper into your data.
How DataHawk Sources Your Data
Understand the difference between public and private data in DataHawk, why some data requires account connections, and typical freshness for each data type.