Concepts of Data Warehousing and customer defined requirements
Data Warehousing design approaches

Architectures, schemas, tuning, loading, etc.

Dimensional modelling

Performance issues
Data lakes

Issues of data cleansing
Data governance
Data integration
Data transformation
Working with structured and unstructured data
Using Data Warehousing techniques with a relational database

WRITTEN: A case study to model a business problem to build as a data warehouse represented as a design report (design documentation, and reasoning for choice of design) - Learning Outcomes 1-2
PRACTICAL PRESENTATION: A small prototype to represent the design modelled within the design report – Learning Outcomes 2- 3

Lectures and Practical sessions:

Lectures will introduce key topics and concepts with tutor-assisted practical sessions. In the practical sessions you will get hands-on experience of the principles taught in the lectures. Academic learning will be achieved through reading around the subject area. Module tutors will suggest useful texts, though many others will be suitable and can be found in our e-library. If you require help understanding any of the concepts, you may contact your module tutor for assistance.

CRITICALLY EVALUATE DOMAIN-SPECIFIC TECHNIQUES FOR CREATION OF DATA WAREHOUSES WITH RESPECT TO DIFFERENT DISCIPLINES.

Knowledge and Understanding, Learning, Enquiry

APPLY APPROPRIATE TECHNIQUES TO THE DESIGN AND CREATION OF A DATA WAREHOUSE

Application

DEVELOP SYSTEMATIC ANALYTICAL APPROACHES TO PROBLEM SOLVING AND DEMONSTRATE THE ABILITY TO INTERPRET, SUMMARISE AND COMMUNICATE THE RESULTS OF DATA ANALYSIS

Analysis, Problem Solving, Communication

Marr, B. (2016) Big data in practice: how 45 successful companies used big data analytics to deliver extraordinary results Wiley ISBN: 1119231388; 9781119231387


Ladley J. (2012) Data Governance: How to Design, Deploy and Sustain an Effective Data Governance Program Morgan Kaufmann ISBN-13: 978-0124158290 0124158293



Krishnan, K. (2013),¿Data warehousing in the age of big data,¿Morgan Kaufmann, Amsterdam.ISBN:
0124059201, 9780124059207 Full text online



Kimball, R. & Ross, M. (2013),¿The data warehouse toolkit: the definitive guide to dimensional modeling,¿3rd;3rd; edn, John Wiley & Sons, Indianapolis, IN. EBOOK ISBN 9781118732281 Full text Online


Inmon, W.H. (1997),¿Data stores, data warehousing and the Zachman framework: managing enterprise knowledge,¿McGraw-Hill, London;New York;.ISBN:
0070314292, 9780070314290



Jorgensen, A. (2014),¿Microsoft big data solutions,¿Wiley, Indianapolis, Indiana.
ISBN:9781118729083, 1118729080



An annually updated keylinks online resource bank will be made available

Suitable development environment e.g. Oracle or SQL Server

This module looks at creating and utilising Data Warehousing techniques and examines two of the most popular styles (Kimball and Inmon). In studying it you will explore Data Warehousing from many angles and topics which include design approaches, architecture, modelling, working with data, cleansing, and data governance.