CA Test Data Manager 3.x: Foundations 200

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Meagan Gibbs
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1 CA EDUCATION COURSE DESCRIPTION CA Test Data Manager 3.x: Foundations 200 Course Overview PRODUCT RELEASE CA Test Data Manager 3.2 This course provides students with primary concepts on each function of the application. In this course students will be taught how CA Test Data Manager (CA TDM) collects, manages and profiles source data to provide a structured and centralized approach to test data management. Students will be able to define and customize data relationships based on business requirements and testing needs. Students will also be taught to navigate to CA TDM tools and reports to further understand and refine data for testing. This Instructor Led Training (ILT) course is based on the OnDemand versions of the courses listed below. COURSE TYPE, LENGTH & CODE Instructor-led Training (ILT) 4 days 88TDM2009T PREREQUISITES General testing background Knowledge of database design fundamentals What You Will Learn This course is comprised of the following courses: CA Test Data Manager: Overview 100 CA Test Data Manager: Data Profiling 200 CA Test Data Manager: Database Subsetting 200 CA Test Data Manager: Data Masking 200 CA Test Data Manager: Data Generation 200 CA Test Data Manager: Test Matching 200 WHO SHOULD ATTEND Quality Assurance/ Testing Manager Test Data Engineer Quality Assurance Engineer/ Tester Business Analyst Compliance Officer Anyone responsible for provisioning test data

2 Overview 100 (4 hours) Module 1: Test Data Manager High Level Overview Define Test Manager Concepts: Profiling Data Models Subsetting Data Masking (or Desensitizing) Test Matching Test Generation Test Data Warehouse Module 2: Initial User Interface Navigation Establishing a connection profile Comparison of source and target SQL windows Creating a project and registering data to the project Viewing a data model using the Diagrammer tool

3 Data Profiling 200 (4 hours) Module 1: Introduction to Profiling Challenges in understanding Data CA TDM Profiling Benefits Profiling Sensitive or Personally Identifiable Information (PII) Module 2: Discovering Metadata Register Source Data Types Define Oracle and Microsoft SQL Server Registration Register.csv files Manage data using object tags Module 3: Refining Data Relationships View table relationships Build and modify relationships Use CA TDM relationship conditions and cardinality Module 4: Discovering Data Content Sample and profile registered data View analyzed data Use filtering to identify PII

4 Database Subsetting 200 (4 hours) Module 1: Database Subsetting Overview Database Subsetting Introduction CA TDM Database Subsetting Benefits Database Types Module 3: Adding and Removing Branches Add a New Link to the Tree CA TDM relationship conditions and cardinality Module 5: Generate Scripts Generating Subset Scripts Referencing Extract Rules Filtering other Tables Adding Optional Scripts Module 7: Run Export Script Export Execution Exported Files Validation Module 2: Preparing the Subset Schema Categorize Tables Maintain Object Tags Launch Database Subsetting Subset Connection Profiles Define Driving Tables Copy Relationships Module 4: Define the Subset Criteria Define Driving Coordination Using the SQL Window Save the Extract to the Repository Module 6: Database Subset Preparation Script Execution Previewing Row Counts Verifying an Empty Schema in CA TDM Module 8: Run Import Script Import Execution Verify Imported Data Review Data Results

5 Data Masking 200 (4 hours) Module 1: Database Masking Overview Database Masking Introduction Challenges in Masking CA TDM Database Masking Benefits Module 2: Creating Connection Profiles Create and Saving Connections Connect to Flat Files Connect to Database Systems Connect to XML files Common Commands and references Module 3: Building a Masking Map Identify PII inside a Data Object Understand Types of Masking Functions Mask Specific Columns of Data Use Seed Data From Files and Database Systems Save Masking Routines Module 4: Set Masking Options Opening, Editing and Saving Masking Routines Set Reporting Options Set Options for Simulated Masking Routines Run Masking Routines in Simulation Mode Module 5: Audit Masking Routines for Database Updates Use an Audit Report to Compare Results Validate Results with Runtime Reports View Database Updates Containing Masked Data

6 Data Generation 200 (8 hours) Module 1: Navigate Data Generation Tools Launch the Data Definition Tool Launch the Data Editor Use the Functions Pane to Formulate Data Use the Columns Pane to Reference Columns Use the Variables Pane to Define Attributes Module 2: Data Generation Basics Data Generation Basics Build a Model Row Edit Data with a Number Function Save Edits and Use Copy Operations Validate Data Using Preview Tool Module 3: Data Generation Functions Function Types for Data Generation Maintain Seed Lists Edit Seed Lists Reference a Seed List Understand Function Properties Use Specific Seed List Columns Publish (Generate) Data Ripple Parameters Through Functions Maintain the Referential Values Of Data Link Column Values with Seed Lists Use Conditional Functions to Edit Data Use Boolean Expressions in Conditional Functions Substitute Variables to Define Data Attributes Use the Creation Assistant for Data Generation Use the Creation Assistant with Subsets

7 Test Matching 200 (8 hours) Module 1: Course Overview Challenges in Test Case Coverage CA TDM Test Matching Benefits Managing Data Objects Creating, Truncating, and Dropping Tables SQL Statements used in this Course Process Flow to Prepare Test Match Module 3: Build a Test Mart Use SQL Statement to Create Test Mart Table Register the Test Mart Module 5: Use a Test Case to Build Test Criteria Link Test Match with Test Criteria Data Pool Build a Data Pool with Test Case Criteria Set Preferences for Test Case Data Pool Module 2: Create a View for Test Mart Use a Test Case to Determine Data Attributes Identify Data Objects Needed for Test Case Determine Data Needed for Test Mart View Use an SQL Statement to Create a View Module 4: Link Test Mart to View Create Data Pool for Test Mart Use SEQLOV functions for Test Mart Use EXECSQLCOUNT function for Row Count Module 6: Prepare and Run a Test Match Run a Test Match Analyze Test Match Results Determine Next Steps for Data Provisioning

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