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The Role of the Data Steward

Data Stewardship is a critical role

Data Stewards fill one of the most critical roles in the in the Data Eco-system, ensuring the accuracy and availability of data, essential in AI environments. They are responsible for implementing and promoting Data Management best-practices for the ethical use of data, enabling operations and supporting intelligence initiatives.

Data Stewards should strengthen the data culture through their passion for data.

Who is a Data Steward?

Data Stewards are usually Subject Matter Experts, with a good understanding of a particular area of the organisation’s data, employees with strong data skills and are among the most valued staff.

Are you one of the Data Champions of your organisation?

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Public courses (online)

Duration: 24 hours
Delivery: 2 options
Full-time for 4 consecutive days
Part-time, one 4-hour session / week, for 6 weeks

Courses are run at different times for these zones:
Central and Eastern Standard Time (CST, EST)
Atlantic Standard Time and Greenwich Meantime (AST, GMT),
Central and Eastern European Time (CET, EET),
Gulf Standard Time (GST)

Private training (online or in-house)

Duration: 24 hours
Full-time over 4 consecutive days, or scheduled as per requirements

*Discounts for groups of +10

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Course overview

In this practitioner’s course delegates will gain a thorough understanding of what is required to be an effective Data Steward, and what is needed to create the data foundation and support business initiatives, such as AI.

This course will cover the following:

  • The role of Data Steward:
    • Who are the Data Owners and Data Stewards?
    • Why do we need Data Stewards?
    • Key responsibilities of a Data Steward
    • What skills does a Data Steward need?
    • What experience does a Data Steward need?
  • What a Data Steward needs to know about:
    • Data Ethics and Compliance
    • Data Privacy, Protection and Security
    • Data Analysis and Interpretation
    • Data Visualisation and Storytelling
    • Metadata Management
    • Data Assessments
    • Data Quality Improvement
    • Monitoring and Measurement
    • Reference and Master Data Management
    • Data Warehousing and Business Intelligence
    • Data Governance
  • What a Data Steward does in a typical day:
    • Data Analysis
    • Issue Resolution
    • Root Cause Analysis
    • Data Correction
    • Reporting
  • Practical exercises to help you become a successful Data Champion:
    • How to communicate more effectively through Data
    • How to get others to appreciate what can be done with Data
    • What to be aware of when assisting others to do more with their Data
    • How to create more interest in Data Management
  • An overview of what else Data Stewards can do to increase their skills and knowledge.

Learning outcomes

After attending this workshop, delegates will be equipped to perform the role of a Data Steward:

  • Managing the processes and procedures required to ensure the quality, control, protection and effective usage of data
  • Delegates will be well-equipped with the knowledge and skills required to assist effectively in all areas of Data Management
  • With practical experience gained from exercises, designed to rehearse being a Data Champion.

* A certificate of attendance will be provided on completion of the course

Intended participants

This is an ideal workshop for anyone who is fulfilling the role of Data Steward or aspiring to.

Why train your team together?

Training a team together creates organisational capability. Transform learning into a shared operational improvement initiative — not just a once-off course.

When teams learn together:

  • Shared understanding of data quality standards and terminology
  • More consistent data practices across the organisation
  • Improved collaboration on data issues and reporting
  • Easier implementation of new data quality processes
  • Stronger accountability and ownership
  • Better communication between business and technical teams
  • Teams return aligned, motivated, and ready to execute

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