Week 1 |
Introductory lecture
Introduces the module, outlining its relevance to the field and connections to other topics. It provides an overview of the content structure, key references, and assessment details. |
Week 2 |
Mastering ETL Processes
Strengthen your ability to integrate and prepare data by mastering ETL processes. Focus on ensuring data quality through cleansing and transformation using tools like Apache NiFi, Talend, and Microsoft SSIS. This foundational skill ensures that the data used in analysis is reliable and accurate, setting the stage for effective business intelligence. |
Week 3 |
Designing Data Warehouses
Build a solid foundation in storing and managing large datasets by designing effective data warehouses. Explore concepts like OLAP, MOLAP, and ROLAP, and learn how to create data marts and schemas. This knowledge enables you to organise data efficiently, supporting robust analytics and timely decision-making. |
Week 4 |
Leveraging Cloud Analytics
Harness the power of cloud-based analytics platforms to handle large-scale data processing and storage. Work with services like Microsoft Azure Synapse Analytics, Google BigQuery, and AWS Redshift. This allows you to scale your business intelligence solutions flexibly, meeting the demands of growing data volumes. |
Week 5 |
Implementing Real-Time Processing
Discover the importance of immediate insights in today's fast-paced business environment. Learn how to implement real-time data processing using tools like Apache Kafka and Apache Flink. This skill enables you to respond swiftly to changing conditions and make timely, informed decisions. |
Week 6 |
Analysing Data Patterns
Uncover meaningful patterns, trends, and correlations within datasets. Use tools like Tableau, Power BI, and Python libraries such as Pandas, NumPy, and Matplotlib. Focus on techniques like regression analysis, clustering, and classification to inform strategic decisions with data-driven insights. |
Week 7 |
Predictive and Prescriptive Analytics
Learn how to leverage machine learning techniques for implementing predictive and prescriptive analytics, with hands-on experience of TensorFlow. Develop models that can forecast future trends and behaviours, empowering proactive business strategies. |
Week 8 |
Exploring Advanced Analytics
Dive deeper into advanced statistical methods and data mining techniques. Explore association rule mining, decision trees, time series analysis, survival analysis, and neural networks using R and Python. This expertise allows you to extract complex insights and uncover hidden patterns in data. |
Week 9 |
Utilising Text Analytics
Expand your analytical toolkit by incorporating natural language processing for text analytics. Use libraries like NLTK and spaCy to analyse unstructured text data. This enables you to gain insights from a wider range of data sources, including documents, social media, and customer feedback. |
Week 10 |
Creating BI Dashboards
Learn to create and deploy interactive business intelligence dashboards. Utilise cloud-based BI services like Google Data Studio and Microsoft Power BI Service, to communicate insights and data narratives to facilitate informed decision-making across the organisation. |