Welcome to the Training Materials Wiki Page!
Training Materials wiki page serves as a centralized repository for all relevant training materials related to our Data Governance (DG) and Data Management (DM) initiatives. Here, you'll find comprehensive resources, including high-level training decks, detailed process guides, and practical templates, designed to support your understanding and application of DG and DM principles.
Whether you're new to these concepts or looking to deepen your expertise, this page provides the tools and knowledge you need to navigate and contribute to our data-driven initiatives effectively.
Key Concepts
Data Management is the development, execution, and supervision of plans, policies, programs, and practices that deliver, control, protect, and enhance the value of data and information assets throughout their lifecycle.
Data Governance is the exercise of authority and control (planning, monitoring, and enforcement) over the management of data assets.
Data Quality refers to the planning, implementation, and control activities that apply quality management techniques to measure, assess, improve, and ensure the fitness of data for use.
Why is Data Governance Important?
Data Governance is the core enabler to become a data-driven organization
Data Governance is the backbone that will drive Solvay to have complete, accurate, secure and timely data, while enabling operational efficiency and becoming more insight-driven.
How are we going to achieve this?
Data Governance Framework
The use of a DG Framework, composed of five elements, helps to organise and structure methods and concepts around DG and tailor them to the specific engagement.
Guiding Policies & Principles
Describes the guiding policies and principles for Data Governance within Solvay.
Roles & Responsibilities
Clear defined roles, responsibilities, organisation structure and committees to enable data governance model to run. Outlines the individuals at Solvay who will direct the application of Data Governance, including the Data Governance Team and Committees.
Processes
Outlines structured workflows and procedures ensuring the Data Governance initiatives are being implemented and deliver value to Solvay.
Tools & Technology
Outlines the available tools required for data governance, such as business catalog and the data quality monitoring tool. These enable efficient implementation and management of governance activities.
Governance Metrics
Outline key performance indicators (KPIs) and success metrics to measure the effectiveness of data governance initiatives.
This training provides an overview of Data Management Foundations, explaining what is Data Management, Data Governance and Data Quality.
Key takeaways include:
What is Data Management ?
Development, execution, and supervision of plans, policies, programs, and practices that deliver, control, protect, and enhance the value of data and information assets throughout their lifecycle.
What is Data Governance?
- Exercise of authority and control (planning, monitoring, and enforcement) over the management of data assets.
What is Data Quality?
- Refers to the planning, implementation, and control activities that apply quality management techniques to measure, assess, improve, and ensure the fitness of data for use.
Data Governance Collaborating Groups
- Data Management Team (Data Governance Lead and Data Governance Team)
- Business (Data Domain Lead, Data Subdomain Lead, Data Owner and Data Steward)
- IT (Data Custodian)
Data Governance Model
- Data Management Steering Committee
- Data Governance Committee
- Data Domain Community