Business Intelligence + Data Warehousing (Level 8)

Duration i year

Stage Award

NFQ Level Level 8

ECTS Credit 5

The module aims to facilitate learners in engaging with the concept of Business Intelligence & Data Warehousing, its formulation and implementation.

The objective of this module is to provide the learner with knowledge of:

The theoretical and practical differences between traditional datasets and Business Intelligence and Data Warehousing datasets
An overview of the initial collection and storage of data
A formal grounding in data intelligence concepts
Apply principles of analytics to solve business problems and inform decision making
Developing knowledge and understanding of dashboards and executive reporting
Applying these techniques and principles in typical real-world scenarios

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Business Intelligence + Data Warehousing (Level 8)

Indicative Syllabus

Foundations of Business Intelligence and Data Warehousing

Defining Business Intelligence and its Application Areas
Data Warehousing Fundamentals: Inmon’s and Kimbel’s Approaches
Data Warehouse Architectures (e.g. Enterprise Data Warehouse, Federated, Enterprise Service Bus, etc.)
Data Models Kimbel’s Front and Back Room Analogy

Analytics for Business Intelligence

Online Analytical Processing (OLAP)
Cube Building
OLAP operations (e.g. Slice, Dice, Roll Up, Drill Down)
Vendor Solutions and Tools for OLAP
Foundations of Data Mining for Business Intelligence

Visualisation and Reporting

Business Reporting
End User Dashboards
Deriving Value from Business Data Reporting Tools and Vendor Solutions

Architecting the Data Warehouse

Business Requirements Engineering Architecture Types (e.g. Hub and Spoke, Centralised, Enterprise Data Warehouse, Independent Data Marts, Enterprise Service Bus, Federated)
Design Methodologies (e.g. Top-down, and bottom-up) Vendor Implementations (e.g. SAP Hana, IBM Cognos, Terradata, Oracle Hyperion, Microsoft SQL Server

Extract, Transform, and Load (ETL)

ETL Pipelines for Structured Data, Data Extraction Methods Data Transformation and Cleaning Techniques Data Loading (e.g. bulk loads, refresh loading etc.) Vendor ETL Tools

Query Optimisation

Planning for performance Pre-compilation, Aggregates ROLAP vs. MOLAP vs. HOLAP Vendor-specific optimisation examples

Module Details

Minimum Intended Learning Outcomes (MIMLOS)

Evaluate the role and benefits of effective business intelligence in the organisation
Demonstrate awareness and critical understanding of developments in data warehouse design and implementation
Demonstrate awareness and critical understanding of developments in business intelligence front end tools and techniques
Independently research current trends and developments in business intelligence related technologies
Apply research methods to their work and differentiate between exploratory, constructive and empirical research
Demonstrate awareness and critical understanding of applications in the areas of ETL, Databases, and BI
Evaluate and critique current legislation on data privacy and relevant ethical issues

Assessments / Exams

The Business Intelligence and Data Warehousing module is assessed by 60% continuous assessment (x 2 CA’s at 30% each) and 40% proctored examination. The use of continuous assessment is based on developing the learner’s ability to investigate, evaluate theories and concepts and apply them to a given scenario.

The 40% Proctored Written Examination will be case study based. The case study will be issued two hours before the examination for review. The examination will be two hours in duration and all questions will be based on the case study. Learners will be required to demonstrate the learning of concepts, theories etc by identifying issues in the case study and offering recommendations, with justifications.

Questions in the examination will be linked requiring learners to complete/attempt the first question before attempting the second and so on.

Mapping of Assessments to Module Learning Outcomes

	MLO 1	MLO 2	MLO 3	MLO 4	MLO 5	MLO 6
Examination		X	X		X
Continuous Assessment	X			X		X

Reassessment Opportunity

Where the combined marks of the assessment and examination do not reach the pass mark the learner will be required to repeat the element of assessment that they failed. Reassessment materials will be published on Moodle after the Examination Board Meeting and will be aligned to the MIMLOs and learners will be capped at 40% unless there are personal mitigating circumstances.

Business Intelligence + Data Warehousing (Level 8)

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