Latest Module Specifications
Current Academic Year 2025 - 2026
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Description Business Analytics 2 follows from Business Analytics 1 and uses a blended learning approach to develop students’ skills in the broad area of “Business Analytics”. In this module students will develop the core statistical skills and more advanced data visualization and MS EXCEL spreadsheet skills required in data driven organsations. Students are also introduced to databases and data management and given an introduction to SQL data querying language. In the second half of the course students are introduced to the developing role and applications of Data Analytics and given an overview of the Data Analytics function in data driven organisations. A unique feature of the module is the option to choose from a selection of Business Analytics topics in the second half of the module. These will vary from topics on developing a Data Analytics strategy to more technical topics like learning a program language (Python or R). Options will also include specialist topics linked to marketing, accountng, finance, aviation and other specialsims. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Learning Outcomes 1. Provide an overview of the 'Business Analytics Function” in an organisation and how it links to other functions and gain an insight into the applications of data analytics in increasing data driven businesses. 2. Explain the nature of sample error and calculate this error for a number of sample parameters 3. Choose the appropriate statistical techniques for testing a variety of statistical hypotheses 4. Build a basic Predictive Analytics model using Linear Regression and test assumptions and limitations of these models 5. Explain the key concepts in Managing Data and databases and use SQL to create basic database queries 6. Develop key analytics skills in their own chosen specialism (e.g Aviation, Marketing, Finance, Accounting,...) 7. Use TABLEAU to create data visualisations and a customised dashboard 8. Use advanced modelling skills in MS EXCEL | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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All module information is indicative and subject to change. For further information,students are advised to refer to the University's Marks and Standards and Programme Specific Regulations at: http://www.dcu.ie/registry/examinations/index.shtml |
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Indicative Content and Learning Activities
Probability Basic Probability - Discrete Probability Distributions; Binomial Distribution, Poisson Distribution - Normal Distribution Statistical Estimation Sampling - Sample Error - Confidence Intervals Statistical/Hypothesis Testing What is a Statistical Test? - Steps in involved in a Statistical Test - Independent Sample t-test, One WAY ANOVA, Chi-Square Test Regression and Forecasting / Predictive Analytics Times Series Models - Linear Regression - Cause and Effect Data Management and Databases Introduction to Databases - Relationship Database Systems - SQL. Tables, Relationships, Joins, Subqueries, Regular Expressions. Big Data and Big Data Management Overview of "Big Data" and Big Data Management Tools Advanced MS EXCEL Finance Functions and Introduction to Valuation using MS EXCEL Calculating Present Values, Calculating NPV, Calculating IRR using MS EXCEL, Investing with Loans, Market Based Valuation and Multiples, Growth Rates and Terminal Values Creating Dashboards in MS EXCEL. Introduction to MS EXCEL Macros Building Models using MS EXCEL Business Models in MS EXCEL Case Study: Building a basic Pricing Model for an Airline using MS EXCEL using Goalseek and SOLVER. Forward Looking Business Models using MS EXCEL Building a Model in MS EXCEL using Decision Trees and Scenario Analysis Discrete Event Simulation Model, Case Study; Overbooking on a Flight using MS EXCEL Specialism Options - Web Analytics Why digital analytics? How Google Analytics works, Google Analytics setup, How to set up views with filters. The Google Analytics Interface; Navigating Google Analytics, Understanding overview reports, Understanding full reports, How to share reports, How to set up dashboards and shortcuts. Basic Reports: Audience reports, Acquisition reports, Behavior reports. Campaign and Conversion Tracking, How to measure Custom Campaign, Tracking campaigns with the URL Builder, Use Goals to measure business objectives, How to measure Google Ads campaigns Specialism Options - Financial Modelling using MS EXCEL Finance Functions and Introduction to Valuation using MS EXCEL Calculating Present Values, Calculating NPV, Calculating IRR using MS EXCEL, Investing with Loans, Market Based Valuation and Multiples, Growth Rates and Terminal Values Specialism Option - Programming in Python Basic Introduction to Python Course - Open source object orientated programming language with many Data Analytics applications. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Indicative Reading List Books:
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Other Resources
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