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This three day course is aimed at Leaders and Managers wishing to take Data Governance to the next level as well as Data Stewards, and Analytical Leads. Additionally, for those involved in Ethical and Legal Governance oversight from across their organisation who may provide input towards a Data Governance Council.

You will be introduced to key data concepts and staff responsibilities, the purpose of Data Governance and scenarios where governance processes are required.

You will gain greater understanding of how wider processes work to support your role in governing the use of data for both ethical purposes and for improving inter-operability across your organisation.

Throughout the course you will be guided through exercises and tasks designed to enable you to plan appropriate policies and procedures for Data Ingestion, Quality and Compliance, Data Storage and Disposal, Reporting and Analysis, Machine Learning, AI and Predictive Modelling, CI/CD and Change Management.

Data Governance is key to progressing the ecosystem of an organisations’ data systems – you will gain knowledge allowing you to identify what stage your organisation is at and the advantages of unlocking and reaching the next step.

You will be able to advise and guide your organisational oversight and procedures to ensure good governance and the identification of challenges, opportunities, and how to create practical solutions through well managed change.

Understanding and Scoping a Data Ecosystem

Introduction to Data Governance
- Identify the Data Lifecycle and the role of key personnel
- Describe the purpose of Data Governance
- Identify scenarios where data governance is required
- Describe the levels of Organisational Data Maturity
Data Ingestion Policies and Procedures
- Identify sources of data, flows, and necessary security
- Describe how to record data processes and workflows
- Classify data and identify rules required for access policies
Quality and Compliance Requirements
- Interpret data quality metrics and sources of internal and external organisational requirements
- Describe the points at which quality checks are required
- Identify how to create organisational data rules including cleaning and acceptance policies
Data Storage and Disposal
- Describe data architectures, modelling and design
- Outline an inventory of data sources and data flows
- Develop policy for documenting and managing content
- Identify development and review processes for data policies

Understanding and Supporting Organisational Data Use

Reporting and Analysis supported by Data Governance
- Describe the need for data warehousing, reference and master data
- Describe the importance of business intelligence for an organisation
- Identify data stewards and reporting frameworks
- Identify key metrics for measuring business objectives and KPIs
- Critique systems for data integration and interoperability
- Interpret Data Governance scorecards
Modelling and Predicting Governance Requirements
- Record features for the prediction of key metrics
- Describe the importance of producing predictive models
- Identify capabilities of machine learning and AI models
- Describe processes for identifying and obtaining valuable features for the development and improvement of predictive models
- Interpret machine learning and AI scorecards

CI/CD, Change Management, and the Future of Data Governance

CI/CD and Change Management
- Categorise the data maturity level of an organisation
- Create a business case for change and identify potential sponsors
- Compare change management models and best practice
- Describe ways to support organisational wide buy-in
- Describe the formation of a Data Governance council and the terms of reference
- Create a communication plan for ongoing changes
- Develop policies and procedures for quality, legal, ethical, and compliance checking prior and during deployment of reporting and analysis processes
- Develop policies and procedures for quality, legal, ethical and compliance checking prior and during model deployment
- List and describe the policies and procedures needed for good data governance
Future of Data Governance
- Review aspects of the roles and responsibilities of those working in Data Governance
- Identify challenges and solutions to improve outcomes from data useage
- Identify emerging roles and responsibilities

Intermediate Data Governance with Essentials Training Course in Hong Kong

Hong Kong is officially known as the Hong Kong Special Administrative Region of the People's Republic of China (HKSAR) and is a city and special administrative region of China on the eastern Pearl River Delta in South China. Hong Kong is one of the most densely populated places in the world, with over 7.5 million population. The official languages of the HKSAR are Chinese and English. Hong Kong is a highly developed territory and ranks fourth on the United Nations Human Development Index and the residents of Hong Kong have the highest life expectancies in the world.

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Intermediate Data Governance with Essentials Training in Hong Kong

Upcoming Trainings

Intermediate Data Governance with Essentials Training in Hong Kong

Outline

Upcoming Trainings