EIEIOTECHNOVATION
← Training programmes

EIEIO / DATA SCIENCE

Data Governance, Management & Stewardship

Course outline

3 days
Discuss this programme →

Duration

Data Governance, Management & Stewardship

3 days

Overview

Data is most likely your organization's most valuable asset. As such, it's not a bad idea to build up a process that ensures it's consistency as well as complies with local regulations surrounding it.In this course, I'll walk you through a high-level overview of everything you need to know to implement a Data Governance program. This course is particularly useful for business leaders that have had issues with data consistency or that need to comply with industry regulations and ensure the security of their customer's data.

Module 1 - The Basics

  • What is Data Management
  • Data Management Subject Areas

Module 2 - Data Governance

  • What is Data Governance
  • Why is Data Governance Important?
  • Examples of what can go wrong without Data Governance
  • Data Governance Core Principles
  • Data Governance Roles and Responsibilities

Module 3 - Data Architecture

  • What is Data Architecture
  • Data Architecure Example
  • Data Architecture Principles
  • Data Architecture main components
  • Data Architecture Frameworks
  • Data Architecture Best Practices
  • Data Architecture Roles

Module 4 - Data Modeling and Design

  • What is Data Modeling
  • Difference between Data Architecture and Data Modeling
  • The 3 Levels of Data Models
  • Conceptual Data Model
  • Logical Data Model
  • Physical Data Model
  • Data Modeling Process
  • Benefits of Data Modeling
  • Data Modeling Tools

Module 5 - Data Storage and Operations

  • What is data storage and operations
  • Why is data storage management important
  • What daily storage management actually involves
  • The 4 key attributes of Data Storage Management
  • Best Practices to keep in mind

Module 6 - Data Security

  • What is Data Security
  • Why is Data Security important
  • Types of Data Security
  • Data Security Risks Intro
  • Accidental Data Exposure
  • Phishing
  • Malware
  • Insider Threats
  • Password Attack
  • Denial-of-Service
  • Man-in-the-Middle (MITM)
  • SQL Injections
  • Zero-day Exploit
  • Best Practices for better Data Security

Module 7 - Data Integration

  • What is Data Integration
  • Example of Data Integration
  • Importance of Data Integration
  • Techniques for Data Integration
  • Manual Data Integration
  • Middleware Data Integration
  • Application Based Integration
  • Uniform Access Integration
  • Common Storage Integration (Data Warehousing)
  • Data Virtulization
  • ETL
  • ELT
  • ETL vs ELT
  • Data Integration Tools
  • Data Integration Best Practices

Module 8 - Document and Content Management

  • What is Document and Content Management
  • Why do we need Document & Conent Management?
  • DMS (Document Management System)
  • CMS (Content Management System)
  • ECMS (Enterprise Content Management System)
  • Best Content Solutions to choose from

Module 9 - Master & Reference Data Management

  • What is Master Data
  • Example of how Master Data works
  • What is Reference Data
  • Example of Reference Data
  • Master Data vs Reference data - how to differentiate
  • Master Data Management (MDM)
  • Why is Master Data Management (MDM) needed/important?
  • How to Implement Master Data Management (MDM) - Step by Step
  • Step 1.1 - Master Data Management Capabilities
  • Step 1.2 - Master Data Management Implementation Styles
  • Step 1.3 - Master Data Management Domains
  • Step 2 - Your current data environment
  • Step 3 - Define your business goals
  • Step 4 - Secure the right sponsorship
  • Step 5.1 - Get the right team
  • Step 5.2 - Get the right tool
  • Step 6 - Implement a quick win
  • Step 7 - Implement and Monitor

Module 10 - Metadata Management

  • What is Metadata
  • Example of Metadata
  • What is Metadata Management
  • Why do we need to manage metadata?
  • Types of metadata Intro
  • Descriptive metadata
  • Structural metadata
  • Administrative metadata
  • Metadata Management tools
  • Implementing Metadata Management

Module 11 - Data Quality

  • What is Data Quality
  • What is Data Quality Management
  • Cost of Poor Data Quality
  • Data Quality Dimensions
  • Data Accuracy
  • Data Validity
  • Data Timeliness
  • Data Completeness
  • Data Uniqueness
  • Data Consistency
  • Data Quality Improvement Process

Module 12 - Data Warehousing and Business Intelligence

  • What is Data Warehousing and Business Intelligence
  • How Data Warehousing and BI work together
  • Data Warehouse
  • Data Warehouse Components
  • Database vs Data Warehouse
  • Data Marts
  • Data Warehouses vs Data Lakes
  • What is Business Intelligence?
  • Business Intelligence vs Business Analytics
  • Applications of Business Intelligence
  • Examples of Business Intelligence
  • BI analysis categories - Descriptive, Diagnostic, Predictive, Presriptive
  • Creating a Business Intelligence Strategy intro
  • BI Strategy Step 1 - Get Sponsorship
  • BI Strategy Step 2 - The BI team
  • BI Strategy Step 3 - Stakeholders
  • BI Strategy Step 4 - BI platforms and tools
  • BI Strategy Step 5 - Define the scope
  • BI Strategy Step 6 - The Roadmap
  • BI Strategy Step 7 - Implementation

BI and big data

  • The importance of self-service within Business Intelligence
  • Business Intelligence Tools

Programme scope, delivery arrangements and suitability are confirmed during enquiry.