Table of Contents
Unit 1: Prerequisites
pagePrereq 101: Why was Data Distiller Built?pagePrereq 102: Key Topics Overview: Architecture, MDM, PersonaspagePrereq 103: DBVisualizer SQL Editor SetuppagePrereq 104: Ingesting CSV Data into Adobe Experience PlatformpagePrereq 105: Ingesting JSON Test Data into Adobe Experience PlatformUnit 2: Data Lake
pageLake 101: Exploring Ingested Batches in a DatasetUnit 3: Real-Time Customer Data Platform
pageProfile 101: Data Distillation for Movie Genre Targeting with Email ListspageProfile 102: Data Enrichment with Derived AttributesUnit 4: Identity Graph
pageID 101: Channel Identity Lookup Table from Profile Attribute Snapshot DatapageID 601: Data Distiller Lambda Functions: Exploring Similarity Joins with Jaccard Similarity MeasureUnit 5: Segmentation
pageAUD 101: Build Segment Overlaps using Profile Attribute Snapshot DatasetsUnit 6: Adobe Journey Optimizer
Unit 7: Insights
pageInsights 102: Creating Your First Table in the Accelerated StorepageInsights 201: Exploring Behavioral Data - Case Study with Adobe Analytics DatapageInsights 202: Web AnalyticsUnit 8: Data Science
pageDS 101: Python & JupyterLab SetuppageDS 102: Basic PythonLast updated