WSQ Data science essentials (SF) (Synchronous and Asynchronous E-Learning)
About This Course
The Data Science essentials module covers relational database development and modern analytics engineering across six instructional units. Learners plan and design normalised relational databases, then implement them to organisational requirements. They progress to Microsoft Fabric, where they build analytical data stores, design and transform analytics data through pipelines, create and manage semantic models for reporting, and prepare AI-ready analytics data using Fabric IQ.
Teaching draws on relational databases with SQL and the Microsoft Fabric analytics platform, spanning OneLake, Fabric Lakehouse, data pipelines using Dataflow Gen2, semantic models, and Fabric IQ. Structured assignments then consolidate the learning, moving from database design, implementation, and testing to hands-on data transformation, modelling, and analytics on practical datasets in Microsoft Fabric.
The module suits fresh graduates and working professionals moving into data engineering and analytics roles. On completion, learners are prepared for job roles such as Analytics Engineer, Business Intelligence Developer, Junior Data Engineer and Database Developer, with cloud analytics skills that are increasingly sought across modern data teams.
What You'll Learn
Instructional Units
1. Database Planning and Design
2. Database Implementation and Testing
3. Analytical Data Stores in Microsoft Fabric
4. Design and Transform Analytics Data in Microsoft Fabric
5. Design and Manage Semantic models in Microsoft Fabric
6. AI-ready analytics data using Fabric IQ
Knowledge Statements:
• Describe database planning and design principles for building normalised, well-structured relational databases.
• Explain how to implement, populate, and query relational databases using SQL.
• Identify analytical data stores, including lakehouses, built in Microsoft Fabric.
• Explain how data pipelines transform and prepare analytics data in Microsoft Fabric.
• Describe how semantic models are designed and managed for reporting in Microsoft Fabric.
• Outline how AI-ready analytics data and ontologies are prepared using Fabric IQ.
Skills Statements:
• Design normalised relational database schemas that meet organisational data requirements.
• Implement and query relational databases using SQL for data operations.
• Build analytical data stores and lakehouses in Microsoft Fabric.
• Transform and prepare analytics data through pipelines in Microsoft Fabric.
• Design and manage semantic models for reporting in Microsoft Fabric.
• Create ontologies and prepare AI-ready analytics data using Fabric IQ.
Entry Requirements
Academic Qualification: Minimum 1 credit in O Level or its equivalent
Experience: Minimum 1 year in any business process