Business Intelligence/Business Analytics

The rise of business intelligence and business analytics has been an influence in the development of data centres. Machines such as the z13 now offer real time analytics in which, for example, the past purchases of a customer can be analysed while a transaction is taking place. Business analytics requires systems which can combine data from a number of sources into one coherent data base against which various kind of analysis can be applied which will support areas such as marketing, strategy development and product development.

We will firstly examine two areas to develop an understanding of the scope and use of business analytics. We will then look at the process of business analytics development, particularly looking the extract, transform and load steps and problems associated with them. We will consider the management issues associated with them and finally extend our studies into the arena of big data.

Tasks

Question 1. Business Intelligence in Education. Explain the concepts of Learning Analytics. Identify a range of data sources which might be used for learning analytics. How might they be combined in a BI application? Comment on a possible data models. Having defined learning analytics, identify the benefits of it. Is learning analytics a disruptive technology? Using a case study, discuss how it might change higher education. Discuss the social and ethical problems associated with learning analytics. Value of learning analytics. Where the data comes from. Social and ethical problems of learning analytics.

Question 2. Business intelligence as a driver of efficiency. Much discussion has centred around BI as a basis for marketing, particularly in focus making on individual customer interests (the demographic of one). However, much of business analytics addresses efficiencies, particularly in areas such as the supply chain and logistics. Using the magazine distribution case study (McBride,N. (2014) Business Intelligence in Magazine Distribution. International Journal of Information Management, 34(1) 58-62) explain how BI can drive efficiency. What are the driving forces which lead to the uptake of BI? How might BI influence relationships with suppliers and customer? Identify and explore management issues around BI, particularly concerning data storage, the ETL lifecycle, buying data and anonymization.

Question 3. Developing Business Intelligence systems. Outline the Analytics life cycle (SAS). Using a case study, explain the steps in a BI methodology. What factors should be considered in evaluating and selection a BI platform? Classify BI users. Do different user groups need different management strategies? Explain what is meant by Extract, Transform, and Load. Does ETL pose problems for the management of information system?

Question 4. Managing Big Data. Define Big Data. Where does it come from, why do companies consider it important? What are the benefits of developing Big Data applications? What are the costs?Explain the 5Vs of Bid Data: Volume, Velocity, Value, Veracity and Variety. What is HADOOP and how it is used? With large volumes of data being distributed and coming into the organisation, what are the management issues? How do we get strategic value out of big data?