Introducing Semarchy xDM (MDM) for Beginners

Complete Semarchy Master Data Management Course

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Last Updated: 2022-06-27 11:06:58 English Course Type: Self Learning

Semarchy xDM installation
Semarchy Data Model
Match and Merge Rules
Web User Interface/Application Design
Integration
Discovery/Source Data Analysis
Dashboards
Security
Workflows
Deployment

This course is for anyone who wants to learn Semarchy xDM. Semarchy Master Data Management and Data Governance, is recognised for the third consecutive year in the Gartner Magic Quadrant for Master Data Management Solutions. This year, Gartner has positioned the Semarchy in the leaders’ quadrant. Semarchy provides features like data quality, data validation, data matching, de-duplication, data authoring, workflows, and more in one single platform.

We will achieve the below in this course:

Installation of Semarchy
Understanding Data Model components and building it step by step
Deploying our data model to Oracle database
Designing our Application which will be used by End Users/Data Stewards
Understanding Semarchy discovery to profile data sources
Creating our first Dashboard with Metrics and charts
Setting up integration with Semarchy
Understanding Security (users and roles)
Workflows for collaboration between different teams

If you have experience in other MDM products and you want to add Semarchy to your profile or you have some knowledge of Semarchy but wants to learn more or you want to create a Semarchy proof of concept(POC) within few hours for a sales pitch, this is the course for you.

We will use all free available resources in this course so you can also have hands on experience with myself during this course. By the end of this course you should be confident to work in any Semarchy implementation.

Basic understanding of MDM concepts
SQL basics

Anyone who wants to learn Semarchy xDM master data management

Section 1 : Introduction 1 Lectures 00:02:54
Lecture 1 :
MDM Introduction Preview
Section 2 : Installation 3 Lectures 00:12:14
Lecture 1 :
Semarchy Installation Part 1
Lecture 2 :
Semarchy Installation Part 2
Lecture 3 :
Post Installation and License
Section 3 : Semarchy Documentation 1 Lectures 00:00:00
Lecture 1 :
Online xDM Documentation
Section 4 : Semarchy Data Model 8 Lectures 01:20:14
Lecture 1 :
Data Model and Entity
Lecture 2 :
Entities(cont.), LOV's and Complex Types
Lecture 3 :
Entities(cont.),References and Diagram
Lecture 4 :
Enrichers and Validations
Lecture 5 :
Match and Merge Part 1
Lecture 6 :
Match and Merge Part 2
Lecture 7 :
Matcher(updated)
Lecture 8 :
Publishers and Survivorship Rules
Section 5 : Deployment 3 Lectures 00:21:22
Lecture 1 :
Datasources
Lecture 2 :
Data Locations
Lecture 3 :
Deployment Process
Section 6 : Design Application 7 Lectures 00:38:50
Lecture 1 :
Introduction to Application
Lecture 2 :
Display Cards
Lecture 3 :
Forms
Lecture 4 :
Collections
Lecture 5 :
Remaining Application Design Components
Lecture 6 :
Application Wizard
Lecture 7 :
Default Application Configuration
Section 7 : Semarchy Integration And Monitoring 9 Lectures 01:27:50
Lecture 1 :
Integration Introduction
Lecture 2 :
Continuous Loads
Lecture 3 :
Load Countries
Lecture 4 :
Load Marital Status
Lecture 5 :
Load Customers
Lecture 6 :
Semarchy Data Hub Structures
Lecture 7 :
Load Customers via Continuous Loads
Lecture 8 :
REST API
Lecture 9 :
Monitoring
Section 8 : Discovery 1 Lectures 00:11:14
Lecture 1 :
Analyse Source Systems
Section 9 : Dashboards 1 Lectures 00:00:01
Lecture 1 :
Creating Semarchy Dashboards
Section 10 : Security 2 Lectures 00:22:21
Lecture 1 :
Users and Roles
Lecture 2 :
Auditing and History
Section 11 : Workflows 1 Lectures 00:00:01
Lecture 1 :
Creating our first workflow
Section 12 : Additional Videos 2 Lectures 00:16:49
Lecture 1 :
Merge,Unmerge from UI
Lecture 2 :
Other Data Model Components

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Rahul Ghai,

2274 Course Views

3 Courses

Information Management professional with experience in multiple data management assignments focusing on Master Data Management, Data Governance, Data Quality, Data Integration, Data Migration and Data Analysis. Extensive experience in working as well as leading multiple data management engagements. Also work in close collaboration with the business stakeholders to ensure successful program delivery.