Utilising a comprehensive framework, participants will gain the knowledge needed to understand core data management concepts and prepare effectively for the DAMA CDMP exam.

Duration:
2 days (On-site or Virtual)

Outline:
Module 1: Introduction & Preparing for the Exam
Module 2: Data Management & DAMA-DMBOK Framework
Module 3: Data Handling Ethics
Module 4: Data Governance
Module 5: Data Architecture
Module 6: Data Modeling and Design
Module 7: Data Storage and Operations
Module 8: Data Security
Module 9: Data Integration and Interoperability
Module 10: Document and Content Management
Module 11: Reference and Master Data
Module 12: Data Warehousing and Business Intelligence
Module 13: Metadata Management
Module 14: Data Quality
Module 15: Big Data and Data Science
Module 16: Data Management Maturity Assessment
Module 17: Data Management and Role Expectations
Module 18: Data Management and Organisational Change Management
Module 19: Mock Exam Review & Q&A

Utilising a structured and interactive approach, participants will explore and apply core data management concepts, preparing for certification and real-world implementation.

Duration:
3 days (On-site or Virtual)

Outline:
Module 1: Introduction & Preparing for the Exam
Module 2: Data Management & DAMA-DMBOK Framework
Module 3: Data Handling Ethics
Module 4: Data Governance
Module 5: Data Architecture
Module 6: Data Modeling and Design
Module 7: Workshop – Creating a Data Governance Charter
Module 8: Data Storage and Operations
Module 9: Data Security
Module 10: Data Integration and Interoperability
Module 11: Document and Content Management
Module 12: Reference and Master Data
Module 13: Metadata Management
Module 14: Workshop – Building a Metadata Catalog Strategy
Module 15: Data Warehousing and Business Intelligence
Module 16: Data Quality
Module 17: Big Data and Data Science
Module 18: Data Management Maturity Assessment
Module 19: Data Management and Role Expectations
Module 20: Data Management and Organisational Change Management
Module 21: Mock Exam Review, Strategy Planning & Q&A

This hands-on workshop introduces participants to the core components of Microsoft Fabric and equips them with the practical skills needed to build modern data analytics solutions.
Participants will explore real use cases, build working solutions, and gain valuable insights from real-world implementations.

Bonus: Delivered by an experienced Fabric implementer who will share tips, best practices, and common pitfalls to avoid when adopting Microsoft Fabric.

Note: Attendees are required to bring their own laptops.

Duration:
2 Days (On-site or Virtual)

Outline:
Module 1: Introduction to Microsoft Fabric
Module 2: OneLake Overview and Ingestion Strategy
Module 3: Hands-On – Ingesting Data with Notebooks and Dataflows
Module 4: Transforming Data Using Notebooks and Dataflows
Module 5: Hands-On – Data Transformation Workflows in Fabric
Module 6: Lakehouse Concepts and Delta Lake Table Management
Module 7: Hands-On – Creating and Managing Delta Lake Tables
Module 8: Power BI Integration and DirectLake Semantic Models
Module 9: Hands-On – Build Dashboards with Power BI + DirectLake
Module 10: Real-Time Analytics and Event Processing in Fabric
Module 11: Hands-On – Designing Real-Time Pipelines
Module 12: Final Recap, Discussion, and Learning Pathways

This 2-day intensive course provides business leaders, IT managers, and data professionals with a hands-on approach to create a comprehensive data strategy for their organisation.

Utilising a 4-step method, participants will learn how to initiate, develop, implement, and sustain a data strategy that aligns with organisational objectives.

Duration:

2 days

Outline:

Module 1: Introduction to Data Strategy
Module 2: Data Strategy Charter Scope Statement
Module 3: Develop Data Strategy
Module 4: Workshop – Create Your Data Strategy Charter and Strategy Document
Module 5: Define Programs of Works
Module 6: Initiate and Sustain Programs of Work
Module 7: Workshop – Defining and Initiating Programs of Work
Module 8: Q&A and Course Recap

This is an official Microsoft course delivered under the Microsoft Certified Trainer program. It covers the various methods and best practices that are in line with business and technical requirements for modelling, visualizing, and analysing data with Power BI.

You’ll learn how to access and process data from a range of data sources including both relational and non-relational. Additionally, this course discusses how to manage and deploy reports and dashboards for sharing and content distribution.

Duration:

2 days

Outline:

Module 1: Get Started with Microsoft Data Analytics
Module 2: Getting Data in Power BI
Module 3: Cleaning, Transforming, and Loading Data in Power BI
Module 4: Design a Data Model in Power BI
Module 5: Create Model Calculations using DAX in Power BI
Module 6: Optimize Model Performance in Power BI
Module 7: Create Reports in Power BI
Module 8: Create Dashboards in Power BI
Module 9: Identify Patterns and Trends in Power BI
Module 10: Create and Manage Workspaces in Power BI
Module 11: Manage Files and Datasets in Power BI
Module 12: Row-level Security in Power BI

Implementing Chat GPT on Azure for Beginners and Non-Data Scientists
Dive into this specialised one-day workshop crafted for professionals looking to understand and utilise Azure’s integration with OpenAI’s leading language models: GPT-4 and GPT-3. Unlock the potential of these AI models and explore how Azure’s infrastructure can elevate their functionalities across different sectors.

In this beginner-friendly OpenAI GPT workshop, participants will:
• Initiate and configure essential Azure services for optimal integration with OpenAI models.
• Gain insights into the unique capabilities and features of both GPT-4 and GPT-3 when implemented on Azure.
• Engage in hands-on tasks using their own dataset (or our provided test data) to witness the real-world impact and applications of these models.
• Understand the intricacies of data storage and management when harnessing the power of GPT models on Azure.
• Learn and apply deployment strategies to ensure the efficient use of the models in real-time scenarios.
• Dive into image generation capabilities, particularly with DALL-E.
• Master a range of applications, from content creation and summarization to advanced semantic search techniques.

By the end of this course, you will:
• Understand the integration and synergy between Azure and OpenAI’s GPT-4 and GPT-3 models.
• Be familiar with setting up and configuring essential Azure services for OpenAI model deployment.
• Recognize the unique functionalities of GPT-4, GPT-3, and the image generation capabilities of DALL-E.
• Apply hands-on knowledge by using your own or provided data with these models, witnessing their real-world applications.
• Understand the data storage and management processes in the context of Azure and OpenAI models.
• Explore diverse AI tasks such as content generation, summarization, semantic search, and image generation.

Duration:

2 days On-site or Online

Outline:

Module 1: Getting Started with Azure Open AI
Module 2: Exploring Azure OpenAI Models
Module 3: Introduction to Prompt Engineering
Module 4: Bringing Your Own Data
Module 5: Data Handling and Storage on Azure

This comprehensive course on Understanding Data Governance arrives at a pivotal moment, a time when data is a company’s most valuable asset. Designed to equip participants with essential knowledge and tools, the course aims to enable your team to implement and oversee data governance practices within your organisation.

Duration:

1 day (Online Only)

Outline:

Module 1: Introduction to Data Governance
Module 2: Foundations of a Data-Centric Organization
Module 3: Advantages and Challenges of Data Governance
Module 4: Best Practices and Objectives of Data Governance
Module 5: Practical Implications of Data Governance
Module 6: Making a Difference in Data Governance

Gain the skills to identify, assess, and improve the quality of your organisation’s data—even without a technical background.

Poor data leads to bad decisions. This practical course gives business users the tools and knowledge to take ownership of data quality and contribute meaningfully to data initiatives across their organisation.

Duration

1 Day (Live, instructor-led – delivered virtually in Microsoft Teams)

What You’ll Learn

This beginner-friendly course introduces the foundations of data quality and empowers you to take action. You’ll explore key concepts such as data quality dimensions, business impact, and improvement techniques—then apply a structured process to manage data quality in real-world contexts.

Modules:

• Basics of Data Quality

• Your Role in Improving Data Quality

• Data Quality Dimensions

• Data Quality Techniques

• Five-Step Process to Improve Data Quality

• Six Practical Data Quality Practices

Includes

Live instruction with real-world examples
Printable course materials and templates
Practical exercises and group discussion
Completion certificate
Post-course Q&A support

This one-day workshop offers participants an introduction to the world of data analytics using Power BI. Designed specifically for beginners, attendees will walk through an end-to-end analytics process – from sourcing and cleaning data to visualisation and insights derivation.

By harnessing the powerful features of Power BI, participants will understand how to transform raw data into meaningful insights using sample HR data.

Duration:

1 day (Online)

Outline:

Module 1: Introduction to Data Analytics
Module 2: The basics and importance of Data Modelling
Module 3: Ingestion and Transformations of Data in Power Query
Module 4: Creating Simple Power BI Reports
Module 5: Common Errors/Troubleshooting Steps
Module 6: The future of Microsoft Fabric and Power BI

This hands-on course aims to provide students with a comprehensive understanding of Data Lakehouse using Databricks, a modern data architecture that merges the capabilities of data lakes and data warehouses.

By the end of the course, students will be well-equipped to design, implement, manage, and optimize a Data Lakehouse for various data storage and analytical needs.

Duration:

2 days

Outline:

Module 1: Introduction to Data Lakehouse
Module 2: Understanding the Underlying Technologies
Module 3: Data Ingestion Strategies
Module 4: Data Storage and Organisation
Module 5: Data Governance and Security
Module 6: Querying and Data Modeling
Module 7: Performance Tuning and Optimisation