Duration: 1h 34m | Video: .MP4 1280x720, 25fps(r) | Audio: AAC, 44100Hz, 2ch | Size: 714 MB
Genre: eLearning | Language: English
In light of the accelerating Digital Transformation across industries in the past years, it has never been more relevant than it is now during the global pandemic that you should improve your digital literacy and upskill yourself with data analytics skillsets.
This course features the latest addition of an organisation structure - Chief Data Office, 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.
At the end of the course, you'll be able to grasp an all-round understanding about below concepts:
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 Quality Management Principles
Data Quality Management Process Cycle
Data Profiling
Data Profiling Technologies (Informatica, Oracle, SAP and IBM)
Metadata
Differences Between Technical and Business Metadata
Business Validation Rules
Data Quality Scorecard (with IDQ example)
Tolerance Level
Root Cause Analysis
Data Cleansing
Data Quality Issue Management
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
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Cantinho Satkeys
