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 “Data Analytics”. In this module students will develop the core Data Analytics statistical skills and more advanced data visualization and MS EXCEL spreadsheet skills.Students are also introduced to Ethics in Data Analytics and Databases, Big Data and Data Management. In Semester 2 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 topics in the second semester. This will vary from topics on developing a Data Analytics strategy to more technical topics like learning a program language like Python. 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 'Data 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. Develop the ability to idenitfy the role of analytics in their own business specialism and identify key analytical tools and skills required by professional in modern data driven organsations in their chosen field 3. Will gain an insight into the ethical and legal obligations and rights required when working with data, including the principles of data protection, GDPR and other data protection rules and ethics in data analytics. 4. Explain the nature of sample error and calculate this error for a number of sample parameters 5. Choose the and apply the appropriate statistical techniques for testing a variety of statistical hypotheses 6. Build a basic Predictive Analytics model using Linear Regression and test assumptions and limitations of these models 7. Explain the key concepts and tools in Managing Data and Databases, including 'Big Data', and use SQL to create basic database queries 8. Use advanced modelling tools including Simulation in MS EXCEL 9. Develop key analytics skills in their own chosen specialism (e.g Aviation, Marketing, Finance, Accounting,...) | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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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
Overview of Business Analytics Keys Steps in a Data Aanlytics Project, Business Intelligence, Role of Analytics in Business, Key SoftwareTools in Business Analytics 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 - Open Source Relationship Database based on SQL. Tables, Relationships, Joins, Subqueries, Regular Expressions. Big Data and Big Data Management Overview of "Big Data" and Big Data Management Building Models using MS EXCEL Business Models in MS Excel Business Modelling fundamentals, Simulation Models Forward Looking Business Models using MS EXCEL Ethics in Business Analytics Ethical and legal obligations when working with data. Principles of data protection, GDPR amd other data protection rules and ethics in data analytics. Specialism Options - 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 Specialism Options - Web Analytics Why digital analytics? How Google Analytics works, Google Analytics setup, 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. Specialism Option - Advanced Visualsation Tools Intermediate Skills in POWER BI and TABLEAU | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Indicative Reading List Books:
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