Exploratory Data Analysis in Data Science Workspace

Platform Tutorials
Introduction to Platform
- A customer experience powered by Experience Platform
- Behind the scenes: A customer experience powered by Experience Platform
- Experience Platform overview
- Key capabilities
- Platform-based applications
- Integrations with Experience Cloud applications
- Key use cases
- Basic architecture
- User interface
- Roles and project phases
Introduction to Real-Time CDP
- Overview
- End-to-end demo
- Workflow
- Overview of B2B Edition
- Orchestrate campaigns with Marketo Engage
Getting started: Data Architects and Data Engineers
Authenticate to Experience Platform APIs
Import sample data to Experience Platform
Administration
- Use alerts
- Use sandboxes
- Copy objects between sandboxes
- Add users
- Add product administrators
- Configure attribute-based access control
Audiences and Segmentation
- Introduction to Audience Portal and Composition
- Upload audiences
- Audience rule builder overview
- Create audiences
- Create content-based audiences
- Create conversion audiences
- Create audiences from existing audiences
- Create sequential audiences
- Create dynamic audiences
- Create multi-entity audiences
- Create audiences with B2B data
- Demo of streaming segmentation
- Evaluate an audience rule
- 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
Audit logs
Data Collection
Dashboards
- Create a dashboard
Data Governance
- Overview
- End-to-end demo
- Classify data using labels
- Create data usage policies
- Enforce data usage policies
- Enforce consent
- Integrate with IAB Transparency and Consent Framework 2.0
Data Hygiene
- Delete datasets
Data Ingestion
- Overview
- Batch ingestion overview
- Create and populate a dataset
- Map a CSV file to XDM
- Sources overview
- Ingest data from Adobe Analytics
- Ingest data from Audience Manager
- Ingest data from cloud storage
- Ingest data from CRM
- Ingest data from databases
- Streaming ingestion overview
- Stream data with HTTP API
- Stream data using Source Connectors
- Web SDK tutorials
- Mobile SDK tutorials
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)
Destinations
- Destinations overview
- Connecting to destinations
- Create destinations and activate data
- Activate profiles and segments to a destination
- Configure a dataset export 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
- Activate through LiveRamp destinations
- Adobe Target and Custom Personalization
- Activate data to non-Adobe applications webinar
Identities
- Identity and identity graphs overview
- Label, ingest, and verify identity data
- View identity graphs
Intelligent Services
- Overview
- Attribution AI overview
- Attribution AI value
- Configure Attribution AI
- Use Attribution AI Scores and Insights
- Customer AI overview
- Customer AI value
- Configure Customer AI
- Use Customer AI Scores and Insights
Monitoring
- Monitor data ingestion
- Monitor segment activation
- Monitor dataflows
Partner data support
- Partner data support overview
- Support offsite prospecting
- Add partner attributes to profiles
- Personalize onsite for unknown visitors
Profiles
- Understanding Real-Time Customer Profile
- Profile overview diagram
- Bring data into Profile
- Customize profile view details
- View account profiles
- Create merge policies
- Union schemas overview
- Create a computed attribute
- Update a specific attribute using upsert
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
- Overview
- Query Service UI
- Query Service API
- Explore Data
- Prepare Data
- Adobe Defined Functions
- Data usage patterns
- Run queries
- Generate datasets from query results
- Tableau
- Analyze and visualize data
- Build dashboards using BI tools
- Recharge your customer data
- Connect clients to Query Service
- Validate data in the datalake
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
Sources
- Sources overview
- Ingest data from Adobe Analytics
- Ingest data from Audience Manager
- Ingest data from Marketo
- Ingest data from cloud storage
- Ingest data from CRM
- Ingest data from databases
- Stream data with HTTP API
- Stream data using Source Connectors
- Troubleshoot: SFTP Connector
Experience Cloud Integrations
- Analytics
- Audience Manager
- Commerce
- Marketo Engage
- Target
Industry Trends
- The Future of Data Management and the Changing Environment
- A Tale of Two Perceptions - Brands vs. Consumers
- Evolving Your Audience Center of Excellence
- Building better experiences with customer profiles
- Data Collaboration in the First-party Data Context

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Exploratory Data Analysis in Data Science Workspace

Last update: 2023-09-25

Topics:
Data Science Workspace
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Created for:
Beginner

User

The Exploratory Data Analysis (EDA) tutorial is designed to assist you with understanding patterns in data, checking data sanity, and summarizing the relevant data for predictive models. For more information, please visit the Exploratory Data Analysis documentation.