Collecting data#
Data collection is the foundation of any successful data analytics workflow. This section guides you through the essential processes and tools for gathering data efficiently and reliably from your various data sources.
Why data collection matters#
Proper data collection delivers accurate, timely, and complete information for your analytics. With Adverity’s data collection capabilities, you can:
Automate data gathering from multiple data sources
Maintain data consistency
Scale your operations
Control your data pipeline
Core concepts#
- What is a datastream?
A datastream is how you collect data from a data source in Adverity. It defines what data to collect, the time period for collection, and how often to collect data.
- What is a data extract?
A data extract is a file that contains the data collected during a fetch.
- What is a Bundle?
A Bundle is a connector that combines data extracts from multiple datastreams into a single data extract.
First steps#
Configuring advanced datastream settings - Configure advanced settings for your datastreams
Working with data extracts - Learn how to manage data extracts with the collected data
Manual and scheduled fetches - Set up automated data collection
Inside this guide#
- Collecting and visualizing non-aggregatable metrics
- Combining data extracts using Bundle
- Configuring advanced datastream settings
- Managing datastreams
- Manual and scheduled fetches
- Using datastream templates
- Using placeholders to name objects
- Working with data extracts
- Viewing datastream issues
- Working with duration data