CDO and Data Quality Accelerator:Strategy to Implementation

In light of the accelerating
AI revolution
across industries in the past years, it has never been more relevant than it is now that you should improve your
digital literacy
and upskill yourself with
data analytics skillsets. [updated in 2024]
This course features the
latest addition
of an organisation structure -
Chief Data Office
which enables an organisation to become data and insights driven, no matter it's in a centralised, hybrid or de-centralised format. You'll be able to understand how each of the Chief Data Office function works and
roles and responsibilities
underpinned each pillar which covers the
key digital concepts
you need to know. There is a focus on the end-to-end
data quality management lifecycle and best practices
in this course which are critical to achieving the vision set out in the
data strategy
and laying the foundations for advanced analytics use cases such as
Artificial Intelligence, Machine Learning, Blockchain, Robotic Automation
etc. You will also be able to check your understanding about the key concepts in the exercises and there are rich reading materials for you to better assimilate these concepts.
At the end of the course, you'll be able to grasp an
all-round understanding
about below concepts:
Digital Transformation
Chief Data Officer
Chief Data Office
Centralised Chief Data Office Organisation Structure
Data Strategy
Data Monetisation
Data Governance
Data Stewardship
Data Quality
Data Architecture
Data Lifecycle Management
Operations Intelligence
Advanced Analytics and Data Science
Data Quality Objectives
6 Data Quality Dimensions and Examples
Roles and Responsibilities of Data Owners and Data Stewards
(Data Governance)
Data Quality Management Principles
Data Quality Management Process Cycle
Data Domain
ISO 8000
Data Profiling
Data Profiling Technologies (Informatica, Oracle, SAP and IBM)
Metadata
Differences Between Technical and Business Metadata
Business Validation Rules
Data Quality Scorecard (with Informatica example)
Tolerance Level
Root Cause Analysis
Data Cleansing
Data Quality Issue Management (with a downloadable issue management log template)
After you complete this course, you will receive a
certificate of completion
.
So how does this sound to you? I look forward to welcoming you in my course.
Cheers,
Bing
Who this course is for:
Students who are interested in learning about the end-to-end data quality management fundamentals and best practices
Students who have non-digital background and would like to explore career opportunities across data analytics disciplines
Students who have technical background and would like to understand from a big picture about how their work fits in a wider digital organisation
Students who would like to understand how Chief Data Office structure works in an organisation
Students who would like to learn about data ownership and data stewardship
Students who are considering applying data quality standards and implement data quality management processes within their organisations
Students who are taking their starting steps out of their studies in the field of data analytics