Migrate Data and Go Live(MB500LP05)

Migrate Data and Go Live
1 Topic
Learning Path Agenda
Module Removed: Prepare Data for Migration
Module 1: Work with Data Management
17 Topics
Objectives
Data Management Concepts
Use Data Entities for Data Management and Integration(1)
Use Data Entities for Data Management and Integration(2)
Work with the Data Management Workspace(1)
Work with the Data Management Workspace(2)
Using Standard and Enhanced Views for Tiles
Use Templates in Data Management – Overview
Use Templates in Data Management – Details
Export, Import, and Copy Data Into a Legal Entity
Demonstration – How to Perform Data Export and Import
Exercise – Explore the Data Management Workspace
Exercise – Export Data Using the Data Management Workspace
Database Movement Operations
Data Sharing Framework
Knowledge Check
Summary
Activity 1
2 Topics
Group discussion: BYOD vs. Entity store, Scenario 1
Group discussion: BYOD vs. Entity store, Scenario 2
Module 2: Perform User Acceptance Testing
13 Topics
Objectives
Introduction
Create User Acceptance Test Libraries
Record Test Cases and Save to BPM
Demonstration – How to Use the Task Recorder to Create a Test Case
Synchronize and Configure your Test Plan in Azure DevOps
Run User Acceptance Tests
Demonstration – How to Create a Test Plan in Azure DevOps to Use with RSAT
Demonstration – How to Use RSAT
Data Task Automation
Exercise – Build Test Scripts to Test Business Functionality
Knowledge Check
Summary
Module 3: Prepare to Go Live
8 Topics
Objectives
Understand the Go-live Process
Complete the Lifecycle Services Methodology
Perform User Acceptance Testing (UAT) for your Solution
Fasttrack Go-live Assessment
Request a Production Environment
Knowledge Check
Summary
Module 4: Use Regression Suite Automation Tool (RSAT)
8 Topics
Objectives
Introduction
RSAT and Reasons to Use it
Create a Test Recording
Install and Configure RSAT
Load Test Cases and Run Automated Tests
Knowledge Check
Summary
Module 5: Work with Analytics and Reporting
10 Topics
Objectives
Introduction
Understand Different Types of Reports and Inquiries
Financial Reporting
Find Inquiries and Reports
Generate and Consume Inquiries and Reports
Configure Finance and Operations Apps for Microsoft Power Platform
Exercise – Work with Reports
Knowledge Check
Summary
Module 6: Configure Electronic Reporting
7 Topics
Objectives
Introduction
Configure Electronic Reporting
Use Barcode Data Sources to Generate Barcode Images
Exercise – Generate Electronic Documents for Payments
Knowledge Check
Summary
Activity 2
1 Topic
Lab 5: Data export using Bring Your Own Database (BYOD)
End Section
1 Topic
Learning Path Recap
Previous Topic

Data Management Concepts

The data management framework consists of the following concepts:​

  • Data entities – A data entity is a conceptual abstraction and encapsulation of one or more underlying tables. A data entity represents a common data concept or functionality, such as customers or vendors. Data entities are intended to be easily understood by users who are familiar with business concepts. After data entities are created, you can reuse them through the Excel add-in, use them to define import/export packages, or use them for integrations.​
  • Data project – A data project is automatically created when you select Import or Export from the workspace and should have at least one job. It contains configured data entities, which include mapping and default processing options. A data project allows users to set up the entities that should be part of the project and defines the format that is used for each entity. It allows users to define the mapping that is used from the source file to the staging and to specify the default processing options.​
  • Data job – Use a data job to perform the actual import or export operation. A data job contains an execution instance of the data project, uploaded files, the schedule or recurrence information, and the processing options to use for the job.​
  • Job history – Histories of source to staging and staging to target jobs. After a job has been run, you can view the job history, which contains the run history for each execution run of the data job and the history of the data move from source to staging and from staging to target.​
  • Data package – Data packages are key concepts for many application lifecycle management (ALM) scenarios, such as copy configuration and data migration. A data package is a single compressed file that contains a data project manifest and data files. A data package is generated from a data job and is used for the importing or exporting of multiple files with the manifest. After you’ve defined a data project, including the data entities and the mapping and sequencing between these data entities, you can create a data package. Then, you can use the data package to move the definition of the data project from one environment to another.​