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This module looks at Business Intelligence from multiple angles, so you as a student get to develop a wide knowledge related to it as a discipline. You will examine Big Data concepts, and data-mining tools such as Orange, as well as compliment your learning with legal and social aspects of the discipline.

1. Plan, develop and test business reporting systems using state of the art visualization and dashboard technologies
Communication, Knowledge and Understanding, Application

2. Query, analyze and develop business data using data mining techniques and web analytics
Analysis

3. Evaluate major principles and techniques of data management and discovery using different applications, processes and technologies
Reflection

Assessment 1 – Students will work on an investigative solution to a Business Intelligence problem and create an analytical report on their findings (Learning Outcomes 1 to 3).

This module provides the skills and concepts necessary to solve problems in Business Intelligence. Topics addressed include the following and represent the state of the art in Business Intelligence:

Big Data Concepts and Technologies
Data mining with open source tools such as Orange
Legal aspects of data including data Privacy and governance
Data Discovery including social media data
Analytical Style and Reports with mathematical underpinning
Data quality including data cleansing and manipulation
Data Visualisation for decision making
Scraping web data with open source tools such as Octoparse

Other than 13 weeks x 3-hour F2F sessions, students are expected to engage in independent study. The independent study will take the form of undertaking follow-up tasks, reading relevant literature, and engaging with online materials through the University’s Virtual Learning Environment (VLE), Blackboard. Students will be expected to keep up to date with current MIS updates and related business and management practices through various websites and academic journals.

The tutor led and peer-to-peer learning sessions will tend to follow a general pattern of introduction of a topic and provision of frameworks and models for student learning, followed by application by students to appropriate data or case study materials. Students will be expected to perform set exercises, these will include the analysis, discussion and presentation of case- based work both individually and as part of a learning group and will receive formative feedback. Students will be expected to obtain supplementary information from a number of paper or electronic sources as part of their preparation, as recommended by the tutor.

All learning will develop and enhance students' digital competences

Sharda, R. (2017), Business Intelligence, Analytics, and Data Science: A Managerial Perspective (4th Edition), Pearson, ISBN-10: 0134633288
Ferrari, A. (2016) Introducing Microsoft Power BI Kindle Edition, ASIN: B01IPIUTTU
Raviv, G. (2018) Collect, Combine, and Transform Data Using Power Query in Excel and Power BI (Business Skills) 1st Edition, Kindle Edition, ASIN: B07HP9J35M

Data analysis tools e.g. Power BI
Software for data mining e.g. Orange
Software appropriate to the issue/problem being investigated e.g. IBM Watson
Data gathering software e.g. Octoparse
WWW
Library
Material on Blackboard.
Staffordshire University has subscriptions to electronic book services such as Safari Tech Books, Ebrary and Netlibrary. There are titles in each of the collections that will support students studying this module. Staffordshire University has subscriptions to IEEExplore, ACM Digital Library, Elsevier Science Direct and Infotrac Computer Database all offering full text electronic access to journals and conference proceedings.