Data Management Masterclass The Complete Course
What you’ll learn
What is Data Management from A to Z
All the different Data Management subject areas
Best Practices on Data Management from the Industry
How to implement Data Management practices within your organization
Requirements
You do not need prior knowledge since we are starting from the basics
Description
**Learn quickly with my Data Management Course that covers the latest best practices from the Data Industry**The course is structured in such a way that makes it easy for absolute beginners to get started! Every Data Management subject area is covered in a separate course section where we will cover all you need to know in terms of processes, people, technology and best practices.This course will give you a deep understanding of the Data Management discipline by using hands-on, contextual examples designed to showcase why Data Management is important and how how to use Data Management principles to manage the data in your organization.In this Data Management course you will learn:· What is Data Management· The different Data Management Subject Areas· Data Governance· Data Architecture· Data Modeling and Design· Data Storage and Operations· Data Security· Data Integration· Document and Content Management· Master & Reference Data Management· Metadata Management· Data Quality· Data Warehousing and Business Intelligence… and a lot of tips and tricks from 10+ years of experience!Enroll today and enjoy:Lifetime access to the course and all future updates10 hours of high quality, up to date video lecturesPractical Data Management course with step by step instructions on how to implement the different techniquesThanks again for checking out my course and I look forward to seeing you in the classroom!
Overview
Section 1: Introduction
Lecture 1 Introduction
Lecture 2 How to get the most out of this course
Section 2: Module 1 – The Basics
Lecture 3 What is Data Management
Lecture 4 Data Management Subject Areas
Section 3: Module 2 – Data Governance
Lecture 5 What is Data Governance
Lecture 6 Why is Data Governance Important?
Lecture 7 Examples of what can go wrong without Data Governance
Lecture 8 Data Governance Core Principles
Lecture 9 Data Governance Roles and Responsibilities
Section 4: Module 3 – Data Architecture
Lecture 10 What is Data Architecture
Lecture 11 Data Architecure Example
Lecture 12 Data Architecture Principles
Lecture 13 Data Architecture main components
Lecture 14 Data Architecture Frameworks
Lecture 15 Data Architecture Best Practices
Lecture 16 Data Architecture Roles
Section 5: Module 4 – Data Modeling and Design
Lecture 17 What is Data Modeling
Lecture 18 Difference between Data Architecture and Data Modeling
Lecture 19 The 3 Levels of Data Models
Lecture 20 Conceptual Data Model
Lecture 21 Logical Data Model
Lecture 22 Physical Data Model
Lecture 23 Data Modeling Process
Lecture 24 Benefits of Data Modeling
Lecture 25 Data Modeling Tools
Section 6: Module 5 – Data Storage and Operations
Lecture 26 What is data storage and operations
Lecture 27 Why is data storage management important
Lecture 28 What daily storage management actually involves
Lecture 29 The 4 key attributes of Data Storage Management
Lecture 30 Best Practices to keep in mind
Section 7: Module 6 – Data Security
Lecture 31 What is Data Security
Lecture 32 Why is Data Security important
Lecture 33 Types of Data Security
Lecture 34 Data Security Risks Intro
Lecture 35 Accidental Data Exposure
Lecture 36 Phishing
Lecture 37 Malware
Lecture 38 Insider Threats
Lecture 39 Password Attack
Lecture 40 Denial-of-Service
Lecture 41 Man-in-the-Middle (MITM)
Lecture 42 SQL Injections
Lecture 43 Zero-day Exploit
Lecture 44 Best Practices for better Data Security
Section 8: Module 7 – Data Integration
Lecture 45 What is Data Integration
Lecture 46 Example of Data Integration
Lecture 47 Importance of Data Integration
Lecture 48 Techniques for Data Integration
Lecture 49 Manual Data Integration
Lecture 50 Middleware Data Integration
Lecture 51 Application Based Integration
Lecture 52 Uniform Access Integration
Lecture 53 Common Storage Integration (Data Warehousing)
Lecture 54 Data Virtulization
Lecture 55 ETL
Lecture 56 ELT
Lecture 57 ETL vs ELT
Lecture 58 Data Integration Tools
Lecture 59 Data Integration Best Practices
Section 9: Module 8 – Document and Content Management
Lecture 60 What is Document and Content Management
Lecture 61 Why do we need Document & Conent Management?
Lecture 62 DMS (Document Management System)
Lecture 63 CMS (Content Management System)
Lecture 64 ECMS (Enterprise Content Management System)
Lecture 65 Best Content Solutions to choose from
Section 10: Module 9 – Master & Reference Data Management
Lecture 66 What is Master Data
Lecture 67 Example of how Master Data works
Lecture 68 What is Reference Data
Lecture 69 Example of Reference Data
Lecture 70 Master Data vs Reference data – how to differentiate
Lecture 71 Master Data Management (MDM)
Lecture 72 Why is Master Data Management (MDM) needed/important?
Lecture 73 How to Implement Master Data Management (MDM) – Step by Step
Lecture 74 Step 1.1 – Master Data Management Capabilities
Lecture 75 Step 1.2 – Master Data Management Implementation Styles
Lecture 76 Step 1.3 – Master Data Management Domains
Lecture 77 Step 2 – Your current data environment
Lecture 78 Step 3 – Define your business goals
Lecture 79 Step 4 – Secure the right sponsorship
Lecture 80 Step 5.1 – Get the right team
Lecture 81 Step 5.2 – Get the right tool
Lecture 82 Step 6 – Implement a quick win
Lecture 83 Step 7 – Implement and Monitor
Section 11: Module 10 – Metadata Management
Lecture 84 What is Metadata
Lecture 85 Example of Metadata
Lecture 86 What is Metadata Management
Lecture 87 Why do we need to manage metadata?
Lecture 88 Types of metadata Intro
Lecture 89 Descriptive metadata
Lecture 90 Structural metadata
Lecture 91 Administrative metadata
Lecture 92 Metadata Management tools
Lecture 93 Implementing Metadata Management
Section 12: Module 11 – Data Quality
Lecture 94 What is Data Quality
Lecture 95 What is Data Quality Management
Lecture 96 Cost of Poor Data Quality
Lecture 97 Data Quality Dimensions
Lecture 98 Data Accuracy
Lecture 99 Data Validity
Lecture 100 Data Timeliness
Lecture 101 Data Completeness
Lecture 102 Data Uniqueness
Lecture 103 Data Consistency
Lecture 104 Data Quality Improvement Process Intro
Lecture 105 Data Quality Improvement Process 1
Lecture 106 Data Quality Improvement Process 2
Lecture 107 Data Quality Improvement Process 3
Lecture 108 Data Quality Improvement Process 4
Lecture 109 Data Quality Improvement Process 5
Lecture 110 Data Quality Improvement Process 6
Section 13: Module 12 – Data Warehousing and Business Intelligence
Lecture 111 What is Data Warehousing and Business Intelligence
Lecture 112 How Data Warehousing and BI work together
Lecture 113 Data Warehouse
Lecture 114 Data Warehouse Components
Lecture 115 Database vs Data Warehouse
Lecture 116 Data Marts
Lecture 117 Data Warehouses vs Data Lakes
Lecture 118 What is Business Intelligence?
Lecture 119 Business Intelligence vs Business Analytics
Lecture 120 Applications of Business Intelligence
Lecture 121 Examples of Business Intelligence
Lecture 122 BI analysis categories – Descriptive, Diagnostic, Predictive, Presriptive
Lecture 123 Creating a Business Intelligence Strategy intro
Lecture 124 BI Strategy Step 1 – Get Sponsorship
Lecture 125 BI Strategy Step 2 – The BI team
Lecture 126 BI Strategy Step 3 – Stakeholders
Lecture 127 BI Strategy Step 4 – BI platforms and tools
Lecture 128 BI Strategy Step 5 – Define the scope
Lecture 129 BI Strategy Step 6 – The Roadmap
Lecture 130 BI Strategy Step 7 – Implementation
Lecture 131 BI and big data
Lecture 132 The importance of self-service within Business Intelligence
Lecture 133 Business Intelligence Tools
Section 14: What Next
Lecture 134 Thank You
Lecture 135 Bonus Lecture
Data Professionals that want to gain complete understanding of Data Management,Managers that need to understand the principles of Data Management,Anyone that wants to have a complete understanding of Data Management
Course Information:
Udemy | English | 10h 9m | 2.78 GB
Created by: George Smarts
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