Course
Business Intelligence
59 hours 53 minutes
Credits: Optional Learning
Description
n this course, learners will build a comprehensive foundation in business intelligence – from infrastructure planning and data modelling through to advanced analytics, AI integration, and generative AI-powered visualisation. Learners will design, implement, and deploy BI infrastructure including ETL pipelines, BI data models, MDX queries, data warehousing, and reporting strategies, and manage availability, recovery, and backup of BI environments. They will explore a broad range of BI tools and analytics platforms including Power BI, Google Cloud, Azure, and Dynamics 365, and apply business analysis frameworks to real-world data challenges. Learners will then develop a strong grounding in generative AI, GPT models, machine learning, deep learning, and prompt engineering, applying these capabilities to Power BI through AI insights, text analytics, machine learning model training, AI-powered visuals, and Copilot. They will also use prompt engineering techniques to manipulate, filter, group, and visualise data with generative AI, and build and refine interactive D3.js visualisations.
What Students Will Learn
- Planning BI Infrastructure
- Designing BI Infrastructure
- Implementing BI Infrastructure
- Extract, Transform, & Load
- Preparing for BI Data Models
- Designing BI Data Models
- BI Data Model Partitions
- BI Reporting & Analysis
- BI Reporting Strategies
- BI Project Deployment
- Integration, Features, & Installation
- Planning & Configuration
- MDX Queries
- MDX Performance
- Availability & Configuration
- Recovery & Backup
- Data Warehousing & Business Intelligence Implementation
- Data Warehousing & Business Intelligence Deployment
- Business Intelligence Tools
- Business intelligence and analytics design for Dynamics 365 solutions
- Foundations of Analytics Literacy
- Essential Business Analytics
- Data Visualization for Business Decision Making
- Unlocking Business Solutions with AI-Powered Analytics
- Google Cloud Digital Leader: Business Intelligence and Data Processing
- Business Intelligence: Project Data Analysis
- BABOK® v3: Business Analysis Perspectives
- Introduction to Power BI
- Azure Data Fundamentals: Power BI for Business Intelligence
- Analyze data with Power BI
- An Introduction to Generative AI
- An Introduction to GPT Models
- Artificial Intelligence and Machine Learning
- Deep Learning and Neural Networks
- Getting Started with Prompt Engineering
- Exploring Prompt Engineering Techniques
- Case Studies in Prompt Engineering
- Considerations for Using AI Responsibly
- Skill Benchmark: Generative AI, Prompting and Ethics Awareness (Beginner)
- Leveraging AI Insights & Text Analytics in Power BI
- Training Machine Learning Models in Power BI
- AI-powered Visuals in Power BI
- Smart Narratives, Q&A Visuals, & Copilot in Power BI
- Skill Benchmark: AI in Power BI Competency (Intermediate Level)
- Prompt Engineering for Data: Leveraging Prompts When Working with Data
- Prompt Engineering for Data: Basic Data Manipulation Using Generative AI
- Prompt Engineering for Data: Leveraging Prompts for Filtering & Grouping Data
- Prompt Engineering for Data: Combining & Visualizing Data Using Generative AI
- Build a D3.js Visualization with Generative AI
- Data Visualization Lab: Visualize the Central Park Squirrel Census with D3.js and Generative AI Part 1
- Troubleshoot and Refine Generative AI Data Visualization
- Data Visualization Lab: Visualize the Central Park Squirrel Census with D3.js and Generative AI Part 2
- Skill Benchmark: Prompt Engineering for Data Science Literacy (Beginner Level)
Overall Learning Outcomes
- Plan, design, and implement BI infrastructure including ETL processes, data models, partitions, and MDX queries
- Deploy and manage BI projects including integration, configuration, availability, recovery, and backup
- Implement data warehousing and business intelligence solutions end-to-end
- Apply BI reporting and analysis strategies to deliver actionable business insights
- Use BI tools including Power BI, Azure, Google Cloud, and Dynamics 365 to analyse and visualise data
- Apply business analysis frameworks and analytics literacy principles to support data-driven decision-making
- Explain generative AI, GPT models, machine learning, deep learning, and neural network concepts
- Apply structured prompt engineering techniques and patterns to data manipulation, filtering, grouping, and visualisation tasks
- Leverage AI capabilities in Power BI including text analytics, machine learning model training, AI-powered visuals, smart narratives, Q&A visuals, and Copilot
- Build and refine interactive data visualisations using D3.js with generative AI assistance
- Apply responsible AI principles to business intelligence and analytics contexts

