Course Code: AOT503
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Synopsis

This course covers key concepts in data management, including relational databases, SQL, and data warehousing. Students will develop practical skills in data visualisation using Python and Tableau to create interactive dashboards and stories. The course also addresses big data technologies like Hadoop, Spark, and modern cloud data platforms, preparing students to manage and analyse large-scale data in AIoT contexts
Level: 5
Credit Units: 5
Presentation Pattern: EVERY JULY

Topics

  • Introduction to Data and Relational Databases
  • Querying Data with SQL (Structured Query Language)
  • Database Design and Normalisation
  • Introduction to Data Warehousing and ETL
  • The Theory and Principles of Effective Visualisation
  • Practical Visualisation with Python Libraries/Tableau
  • Advanced Visualisation and Interactivity
  • Dashboards and Storytelling with Data
  • The Big Data Challenge: Volume, Velocity, and Variety
  • The Big Data Ecosystem: HDFS, MapReduce, and Spark
  • Building Big Data Pipelines
  • The Modern Data Stack: Cloud Warehouses and Lakehouses

Learning Outcome

  • Assess modern data architectures including cloud data warehouses and lakehouses to manage AIoT data ecosystems effectively.
  • Evaluate big data frameworks such as Hadoop and Spark to build efficient data processing pipelines.
  • Develop scalable data warehouses and ETL processes to support comprehensive data integration.
  • Design relational databases applying normalisation techniques to enhance data integrity and efficiency.
  • Construct advanced SQL queries to extract, transform, and analyse complex datasets for informed decision-making.
  • Create sophisticated and interactive visualisations and dashboards using Python libraries and Tableau to communicate insights effectively.
Part-time Programmes / CET Courses