Upskill your people and teams to improve your digital maturity
Digital maturity is not defined by how much technology an organisation owns. It is defined by how confidently its people can use data to make decisions, solve problems and drive measurable impact. Most businesses still have a gap between the tools they have invested in and the skills required to turn those tools into value.
Our training programme closes that gap. Each session builds practical capability in the areas that matter most: strategy, governance, quality and modelling. The focus is clarity, confidence and real outcomes. No noise. No unnecessary complexity. Just the knowledge teams need to work smarter, reduce risk and deliver more value from the digital foundations you already have.
If you want your organisation to operate with stronger insight, faster decision making and a shared understanding of how data creates advantage, this is the starting point.
Training & Enablement
Data Strategy vs Data Governance
Length: 1 hour
Defining strategy versus governance and linking data to Gate 1: Business Outcomes.
Building a Data Strategy Roadmap
Length: 1 hour
Practical steps for vision setting, current state assessment and creating a realistic roadmap.
Key Pillars of a Modern Data Strategy
Length: 1 hour
Exploring culture, analytics, architecture and data monetisation as core pillars.
Connecting Strategy to Operations
Length: 1 hour
How Strategy (Gate 1) triggers Governance (Gate 7) and is measured by Quality (Gate 3).
Data Governance Fundamentals
Length: 1 hour
Core concepts of Governance (Gate 7), key principles and the 8-Gate Framework.
Ownership and Stewardship
Length: 1 hour
Defining Data Owner, Steward and Custodian roles and how they work together.
Data Forums and Communication
Length: 1 hour
Structuring Governance Councils and working groups aligned to Gate 8: Communication.
Metadata Management
Length: 1 hour
The role of business glossaries, data dictionaries and data catalogues in governance.
Policies and Standards
Length: 1 hour
How to create, approve and enforce practical policies and standards for data.
Issues Management
Length: 1 hour
The formal process for logging, tracking and prioritising data issues.
Root Cause Analysis
Length: 1 hour
Investigation techniques (Gate 4) to identify the true source of data errors.
Foundations of Data Quality
Length: 1 hour
Defining fit for purpose and exploring the six dimensions of Data Quality.
Data Quality Assessment and Profiling
Length: 1 hour
How to measure quality (Gate 3: Assessment), profile data and build scorecards.
Data Remediation and Cleansing
Length: 1 hour
Reactive fixes (Gate 6: Remediation) and practical techniques for cleansing bad data.
Data Quality Improvement
Length: 1 hour
Proactive fixes (Gate 5: Improvements) using Root Cause Analysis to improve upstream processes.
Data Quality Monitoring and Reporting
Length: 1 hour
Setting up dashboards and automated monitoring to keep data clean over time.
Building the Business Case and Vision
Length: 1 hour
Securing buy in, defining ROI, setting the mission and linking to Gate 1: Business Outcomes.
Designing the Operating Model
Length: 1 hour
Choosing centralised or federated models, designing the DG Office and defining Gate 7 structures.
The DG Roadmap and Prioritisation
Length: 1 hour
How to start small, select pilot projects and create a phased rollout plan.
Measuring Success and Maturity
Length: 1 hour
Defining KPIs, using maturity models and demonstrating value linked to Gate 8: Communication.
Tool Scoping and Vendor Selection
Length: 1 hour
Defining requirements, running RFI or RFP processes and evaluating governance tool vendors.
Technical Implementation and Integration
Length: 1 hour
Initial setup, connecting to data sources, configuring single sign on and user permissions.
Populating the Tool
Length: 1 hour
Strategies for automated and manual population of the business glossary, lineage and DQ rules.
Driving Adoption and User Training
Length: 1 hour
The change management plan to ensure stewards and users make the tool part of daily work.
Foundations of Data Modelling
Length: 1 hour
Why we model data and how conceptual, logical and physical models fit together.
Relational Modelling (ERD)
Length: 1 hour
Entities, attributes, relationships and the basics of normalisation (1NF, 2NF, 3NF).
Dimensional Modelling (Star Schema)
Length: 1 hour
Facts, dimensions and designing star versus snowflake schemas for analytics.
No courses match your search. Try a different keyword or clear the filters.
