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- Overview
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- Load data in JupyterLab notebooks
- Query and discover data in JupyterLab notebooks
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- Build a model using the recipe builder template
- Analyze model performance
- Create and publish a trained model (UI)
- Schedule automated training and scoring for a service
- Enrich Real-time Customer Profiles with machine learning insights
- Package source files into a recipe
- Import a packaged recipe (UI)
- Import a packaged recipe (API)
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- Destinations overview
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- Integrate with Google Customer Match
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- Configure file-based cloud storage or email marketing destinations
- Configure a social destination
- Activate data to non-Adobe applications webinar
- Identities
- Profiles
- Privacy
- Introduction to Privacy Service
- Identity data in Privacy requests
- Privacy JavaScript library
- Privacy labels in Adobe Analytics
- Getting started with the Privacy Service API
- Privacy Service UI
- Privacy Service API
- Subscribe to Privacy Events
- 10 considerations for Responsible Customer Data Management
- Elevating the Marketer’s Role as a Data Steward
- Queries
- Schemas
- Segments
- Segment Builder Overview
- Create segments
- Create content-based segments
- Create conversion segments
- Create segments from existing segments
- Create sequential segments
- Create dynamic segments
- Create multi-entity segments
- Create segments with B2B data
- Demo of streaming segmentation
- Evaluate a segment
- Create a dataset to export data
- Sources
- Application Services
- Intelligent Services
- Experience Cloud Integrations
- Industry Trends
Understanding data usage patterns with Query Service
This video shares tips and best practices for running queries in the query editor interface, PSQL clients, business intelligence (BI) solutions and the HTTP API.
INFO
This video is part of a course Create Dashboards Using Query Service, available for free on Experience League!
For more information, please visit the query service documentation.
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