Data Quality Masterclass – The Complete Course

Course Curriculum

Chapter 1: Introduction

Lecture 1: Introduction

Lecture 2: Download the Course Resources

Lecture 3: Certificate of Completion – how to get it

Chapter 2: The Basics

Lecture 1: What is Data Quality?

Lecture 2: What is Data Quality Management?

Lecture 3: The Impact of Poor Data Quality

Lecture 4: Estimations on Cost of Poor Data Quality

Lecture 5: Data Quality Issue from real world case studies

Lecture 6: Why do we have bad data?

Chapter 3: 6 Key Data Quality Dimensions

Lecture 1: What is a Data Quality Dimension?

Lecture 2: Data Accuracy

Lecture 3: Data Validity

Lecture 4: Data Timeliness

Lecture 5: Data Completeness

Lecture 6: Data Uniqueness

Lecture 7: Data Consistency

Chapter 4: Data Quality Rules

Lecture 1: What are Data Quality Rules

Lecture 2: Steps to Implement your own Data Quality Rules

Lecture 3: Example of implementing Data Quality Rules

Lecture 4: Data Quality Rules – Example 2

Chapter 5: Data Quality Techniques/Tools

Lecture 1: Data Profiling – What is it?

Lecture 2: Data Profiling – use cases

Lecture 3: Data Parsing

Lecture 4: Benefits of Data Parsing

Lecture 5: Data Standardization

Lecture 6: Identity Resolution

Lecture 7: Identity Resolution Process

Lecture 8: Identity Resolution Benefits

Lecture 9: Data Linkage

Lecture 10: Data Cleansing

Lecture 11: Data enhancement

Lecture 12: Data inspection and monitoring

Chapter 6: Data Quality Roles

Lecture 1: Data Quality Roles intro

Lecture 2: Data Quality Manager

Lecture 3: Data Quality Analyst

Lecture 4: Data Owner

Lecture 5: Data Steward

Lecture 6: Data Custodian

Lecture 7: Data consumer

Chapter 7: Data Quality Process

Lecture 1: The Data Quality Management process

Lecture 2: Step 1 – Define the Data Quality Improvement goals

Lecture 3: Step 2 – Data Profiling

Lecture 4: Step 3 – Conduct Data Quality Assessment

Lecture 5: Step 3 addition – Using Root Cause Analysis Tools

Lecture 6: Step 4 – Resolve Data Quality Issues

Lecture 7: Step 5 – Monitor and Control

Chapter 8: Data Quality Tools

Lecture 1: Why Data Quality Tools are important?

Lecture 2: What is important in a Data Quality Tool?

Lecture 3: The Magic Quadrant for Data Quality Solutions by Gartner

Lecture 4: Informatica

Lecture 5: IBM

Lecture 6: SAP

Lecture 7: Talend

Lecture 8: Precisely

Lecture 9: Ataccama

Lecture 10: How to choose the right Data Quality Tool?

Chapter 9: Optional Section – Data Governance

Lecture 1: Why invest time learning about Data Governance?

Lecture 2: What is the difference between Data Governance and Data Quality

Lecture 3: Data Governance Definition

Lecture 4: Why do you need Data Governance

Lecture 5: Data Governance Gone Wrong

Lecture 6: Data Governance Core Principles

Lecture 7: Data Governance Roles & Respnsibilities

Chapter 10: Data Quality Best Practices

Lecture 1: Top 5 Best Practices to implement

Chapter 11: Optional Section – Example of a Data Quality Tool

Lecture 1: Intro

Lecture 2: Setting up your account

Lecture 3: The Interface

Lecture 4: Connect to Data

Lecture 5: Running Jobs

Lecture 6: Job options

Lecture 7: Overview of Data Quality Scoring

Lecture 8: Data Profile page

Lecture 9: Shapes

Lecture 10: Duplicates

Lecture 11: Schema

Lecture 12: Record

Lecture 13: Source

Lecture 14: Pattern

Lecture 15: How to adjust the features

Lecture 16: Outliers

Lecture 17: Rules

Lecture 18: Data Behaviour

Lecture 19: Outro

Chapter 12: What Next