Enterprise Data Preparation

onDemand | Data Catalog | Self-Paced | Version 10.5.1

Course Overview

Gain the required knowledge and skills to transform, cleanse, and enrich data in the data lake using an Excel-like spreadsheet interface in a self-service manner. Using Informatica Enterprise Data Preparation (EDP), publish and share knowledge with the rest of the community to analyze the data using third-party BI or analytic tools. Applicable to version 10.5.1.


After successfully completing this course, students should be able to:

  • Understand the architecture and components of EDP
  • Configure the EDP application services
  • Prepare the model repository service for use with EDP
  • Configure a Hive resource to represent the data lake
  • Search the catalog for data that resides in and outside the data lake
  • Discover the lineage and relationships between data that resides in different enterprise systems
  • Create and add data assets to the project
  • Explore data in the worksheets
  • Apply the data preparation steps to sample, combine, cleanse, transform and mask the data
  • Publish the prepared data to the data lake
  • Save the recipe as a mapping
  • Operationalize the mapping
  • Schedule and monitor publication
  • Share the published data with other collaborators
  • Analyze the data using third party BI or analytic tools

Target Audience

  • Data Analyst
  • Business User


  • None
Module 1: Enterprise Data Preparation Overview
  • Major Business Challenges
  • Overview of Enterprise Data Preparation
  • Overview of Data Discovery and Analysis Process
  • Architecture & Components
  • Enterprise Data Preparation Concepts
    • Data Lake
    • Data Asset
    • Projects, Worksheets, and Recipes
    • Data Publication
    • Data Visualization
  • User Tasks overview
  • Lab: Getting Started
Module 2: EDP Administration Overview and Tasks
  • Role of an Administrator in EDP
  • Tasks of an Administrator in EDP
  • Tools used by the Administrator in EDP
  • Lab: Configure EDP Service
Module 3: Discover Data
  • Search for Data Assets
  • Data Asset Views
    • Overview view
    • Data Preview
    • Lineage and Impact View
    • Relationships
  • Lab: Understand the Home Page and View Assets
Module 4: Work with Data Assets
  • Upload a Data Asset
    • Uploading a File Directly to the Data Lake
    • Uploading a File with CLAIRE® Discovered Structure
    • Uploading a File with User Defined Structure
  • Import a Data Asset
  • Export a Data Asset
  • Download a Data Asset
  • Delete Data Assets
  • Create and Manage Projects
  • Add assets to the project
  • Lab: Upload and Download a Data Asset
  • Lab: Import and Delete a Data Asset
  • Lab: Create a Project
Module 5: Prepare Data
  • Data Sampling Overview
    • Sampling Table Data
    • Applying Filters
    • Sampling JSON Files
  • Explore Data in the Worksheet
    • Worksheet overview
    • Column overview
  • Data Blending
    • Joining Worksheets
    • Merging Worksheets
    • Using Lookup
  • Categorize Data
  • Using Formulas
  • Using Recipes
  • Summarize Data
    • Aggregate Data
    • Pivot Operation
  • Using Rules
    • Passive Rules
    • Active Rules
  • Using Window Functions
  • Apply One Hot Encoding
  • Lab: Sample and Filter Data
  • Lab: Explore Data in the Worksheets
  • Lab: Blend Data in the Worksheets
  • Lab: Categorize Column Data
  • Lab: Using Formulas
  • Lab: Transformation of Data
  • Lab: Pivot Data
  • Lab: Aggregate Data
  • Lab: Apply rules 
  • Lab: Apply Window function
  • Lab: One Hot Encoding
Module 6: Publish Data
  • Data Publication Overview
  • Scheduling Overview
  • Saving a Recipe as a Mapping
  • Operationalize a Mapping
  • Lab: Publish prepared Worksheets
  • Lab: Schedule a Publication of a Worksheet
  • Lab: Save recipe as a Mapping
  • Lab: Operationalize Mapping
Module 7: Data Visualization
  • Data Visualization Overview
  • Prerequisites Overview
  • Create and Share a Notebook
  • Lab: Create Apache Zeppelin notebook for Visualization

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