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Data Quality Masterclass - The Complete Course

Data Quality Management

Business

Business Analytics & Intelligence

Data Quality Masterclass - The Complete Course

Learn Data Quality Management from A to Z. This complete guide covers all Data Quality Principles, Techniques and more

4.5

(4039)

19045 enrolled on this course

Last updated 11/2021

George Smarts

₹ 3099.0

₹ 4599.0

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30-Day Money-Back Guarantee

Lessons

Quizzes

Duration

13 Hours

Skill level

Beginner

Language

English

Certificate

Yes

Full lifetime access

Yes

Description

Learn
quickly with

my
Data Quality Management
course

that covers the
latest best practices from the Data Industry
The course is structured in such a way that makes it easy even for absolute beginners to get started!
This course will give you a deep understanding of the Data Quality Management discipline by using
hands-on, contextual examples
designed to showcase
why

Data Quality is important and
how
how to use Data Quality principles to manage the data in your organization.
In this Data Quality course you will learn:
·
What is Data Quality
· What is Data Quality Management
· Why is Data Quality Important and how it affects your business
· What are the different Data Quality Dimensions
· What are Data Quality Rules
·
Profiling
· Data Parsing
· Data Standartization
·
Identity resolution
· Record linkage
· Data cleansing
· Data enhancement
· What is the Data Quality Process
·
What are the different Data Quality Roles
· Data Quality Tools and their importance
· Data Quality Best practices
and much, much more!
Enroll today and enjoy:
Lifetime access
to the course
6 hours
of high quality, up to date video lectures
Practical Data Quality course
with step by step instructions on how to implement the different techniques
Thanks again for checking out my course and I look forward to seeing you in the classroom!
Who this course is for:
Professionals working in a data organization
Professionals that want to undertand what is Data Quality and how it can help their organization
Data Management professionals
Management that wants to gain knowledge in the importance of Data Quality Management
Anyone that wants to learn about Data Quality and add another skill to their resume

What you'll learn

What is Data Quality and why it is important

What are the different Data Quality Management techniques

What are the different Data Quality Dimensions

What are the important roles within Data Quality Management

Best Practices from the Industry

Requirements

You will need a copy of Adobe XD 2019 or above. A free trial can be downloaded from Adobe.
No previous design experience is needed.
No previous Adobe XD skills are needed.

Course Content

27 sections • 95 lectures

Expand All Sections

1-Introduction

1.1-Introduction

1.2-Download the Course Resources

1.3-Certificate of Completion - how to get it

2-The Basics

2.1-What is Data Quality?

2.2-What is Data Quality Management?

2.3-The Impact of Poor Data Quality

2.4-Estimations on Cost of Poor Data Quality

2.5-Data Quality Issue from real world case studies

2.6-Why do we have bad data?

2.7-[QUIZ] Data Quality Basics

3-6 Key Data Quality Dimensions

3.1-What is a Data Quality Dimension?

3.2-Data Accuracy

3.3-Data Validity

3.4-Data Timeliness

3.5-Data Completeness

3.6-Data Uniqueness

3.7-Data Consistency

3.8-[QUIZ] Data Quality Dimensions

4-Data Quality Rules

4.1-What are Data Quality Rules

4.2-Steps to Implement your own Data Quality Rules

4.3-Example of implementing Data Quality Rules

4.4-Data Quality Rules - Example 2

4.5-[QUIZ] Data Quality Rules

5-Data Quality Techniques/Tools

5.1-Data Profiling - What is it?

5.2-Data Profiling - use cases

5.3-Data Parsing

5.4-Benefits of Data Parsing

5.5-Data Standardization

5.6-Identity Resolution

5.7-Identity Resolution Process

5.8-Identity Resolution Benefits

5.9-Data Linkage

5.10-Data Cleansing

5.11-Data enhancement

5.12-Data inspection and monitoring

5.13-[QUIZ] Data Quality techniques

6-Data Quality Roles

6.1-Data Quality Roles intro

6.2-Data Quality Manager

6.3-Data Quality Analyst

6.4-Data Owner

6.5-Data Steward

6.6-Data Custodian

6.7-Data consumer

6.8-[QUIZ] Data Quality Roles

7-Data Quality Process

7.1-The Data Quality Management process

7.2-Step 1 - Define the Data Quality Improvement goals

7.3-Step 2 - Data Profiling

7.4-Step 3 - Conduct Data Quality Assessment

7.5-Step 3 addition - Using Root Cause Analysis Tools

7.6-Step 4 - Resolve Data Quality Issues

7.7-Step 5 - Monitor and Control

8-Data Quality Tools

8.1-Why Data Quality Tools are important?

8.2-What is important in a Data Quality Tool?

8.3-The Magic Quadrant for Data Quality Solutions by Gartner

8.4-Informatica

8.5-IBM

8.6-SAP

8.7-Talend

8.8-Precisely

8.9-Ataccama

8.10-How to choose the right Data Quality Tool?

9-Optional Section - Data Governance

9.1-Why invest time learning about Data Governance?

9.2-What is the difference between Data Governance and Data Quality

9.3-Data Governance Definition

9.4-Why do you need Data Governance

9.5-Data Governance Gone Wrong

9.6-Data Governance Core Principles

9.7-Data Governance Roles & Respnsibilities

10-Data Quality Best Practices

10.1-Top 5 Best Practices to implement

11-Optional Section - Example of a Data Quality Tool

11.1-Intro

11.2-Setting up your account

11.3-The Interface

11.4-Connect to Data

11.5-Running Jobs

11.6-Job options

11.7-Overview of Data Quality Scoring

11.8-Data Profile page

11.9-Shapes

11.10-Duplicates

11.11-Schema

11.12-Record

11.13-Source

11.14-Pattern

11.15-How to adjust the features

11.16-Outliers

11.17-Rules

11.18-Data Behaviour

11.19-Outro

12-What Next

12.1-Thank You

12.2-Bonus Lecture

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