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- Ingest data from Adobe Analytics
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- Streaming ingestion overview
- Stream data with HTTP API
- Stream data using Source Connectors
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- Data Science Workspace
- Overview
- Architecture
- Load data in JupyterLab notebooks
- Query and discover data in JupyterLab notebooks
- Exploratory Data Analysis
- Recipes, models, and services overview
- 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
- Connecting to destinations
- Create destinations and activate data
- Activate profiles and segments to a destination
- Integrate with Google Customer Match
- Configure the Azure Blob destination
- Configure the Marketo destination
- Configure file-based cloud storage or email marketing destinations
- Configure a social destination
- Next-hit personalization with Adobe Target
- Activate data to non-Adobe applications webinar
- Identities
- Monitoring
- Profiles
- Privacy and Security
- 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
- Set up customer-managed keys
- 10 considerations for Responsible Customer Data Management
- Elevating the Marketer’s Role as a Data Steward
- Queries
- Schemas
- Overview
- Building blocks
- Plan your data model
- Convert your data model to XDM
- Create schemas
- Create schemas for B2B data
- Create classes
- Create field groups
- Create data types
- Configure relationships between schemas
- Use enumerated fields and suggested values
- Copy schemas between sandboxes
- Update schemas
- Create an ad hoc schema
- 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
- Segment Match connection setup
- Segment Match data governance
- Segment Match configuration flow
- Segment Match pre-share insights
- Segment Match receiving data
- Sources
- Application Services
- Intelligent Services
- Experience Cloud Integrations
- Industry Trends
Data Science Workspace architecture overview
This video walks through an overview diagram and explains the primary components of Experience Platform as it relates to Data Science Workspace.
INFO
This video is part of a course, Getting Started with Data Science Workspace for Data Scientists, available for free on Experience League!
For more information, please visit the Data Science Workspace documentation.
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