Registry
Module Specifications
Archived Version 2022 - 2023
| |||||||||||||||||||||||||||||||||||||
Description The main objective of this module is develop an understanding of the management of analytics projects and to introduce the student to the fundamental tools and techniques of using data and communicating insights to inform management decisions. The module will introduce a variety of approaches for framing analytical problems and projects including CRISP-DM and the EMC Data Lifecycle, as well as project management and communication approaches and considerations. Students will develop their understanding and practical skills in preparing, visualising and analysing structured and unstructured data. Students will be exposed to the principles of data science and analytics and equipped with a variety of tools and techniques to prepare, visualise and analyse data. Common analytics problems will be explored using Excel (Solver), SQL, Tableau, R and other commonly used tools, programming languages and techniques. | |||||||||||||||||||||||||||||||||||||
Learning Outcomes 1. Understand the key concepts of data analytics, the characteristics of big data and how organisations can make use of them. 2. Understand different data preparation, visualisation and analysis techniques and explain the benefits and limitations of different techniques. 3. Evaluate, select and apply appropriate tools, techniques and frameworks to analyse a complex business-related issue. 4. Understand, identify, analyse and assess the legal, regulatory and ethical risks associated with analytics projects. 5. Evaluate, select and apply appropriate project management methodologies and techniques to manage a data analytics project. 6. Prepare and cost a detailed project plan for an analytics project including a data management plan. | |||||||||||||||||||||||||||||||||||||
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 |
|||||||||||||||||||||||||||||||||||||
Indicative Content and
Learning Activities Introduction to Project ManagementKey concepts in project management including starting and initiating a project, controlling a stage, managing product delivery, managing a stage boundary, directing and closing a project.Managing data analytics projectsDeploying the a data analytics management framework (e.g. EMC Data Lifecycle), reframing a business challenge as an analytics challenge, selecting appropriate data visualizations to clearly communicate analytic insights to business sponsors and analytic audiences.Requirements Life Cycle ManagementIntroduce the process to manage and maintain requirements and design information from inception to retirement.Strategy analysisAlign business analytics projects to the business need and strategic objectives of the organisation.Solution EvaluationUnderstand how to assess the performance of and value delivered by analytics solutions deployment within the organisation, and how to identify potential barriers or constraints that prevent the full realisation of the value.Analytics and modelling using ExcelExcel Data Analysis Toolpak, Basic Statistics using Excel, Basic Modelling in Excel, Solving linear optimisation problems using Excel SolverPreparing an Analytics Project PlanDocumenting an analytics project plan, resourcing and budgeting analytics projects, preparing a data management and data breach response plan.Data Analytics using RData structure, working with data frames, and introduction to R functions.Visual Analytics and Data Visualisation using TableauTables, charts and dashboards using Tableau.Data Preparation and VisualisationBest practices in data cleaning, anomalies detection, and normalisation. Basic and advanced visualisation techniques. | |||||||||||||||||||||||||||||||||||||
| |||||||||||||||||||||||||||||||||||||
Indicative Reading List
| |||||||||||||||||||||||||||||||||||||
Other Resources 27577, Online Tutorial, Tableau, 0, Free Training Videos, https://www.tableau.com/learn/training, 27578, Online Tutorial, DataCamp, 0, Introduction to R, https://www.datacamp.com/courses/free-introduction-to-r, 43403, Online Tutorial, Kubicle, 2020, Kubicle BI and Data Analytics Library, Kubicle, | |||||||||||||||||||||||||||||||||||||
Programme or List of Programmes | |||||||||||||||||||||||||||||||||||||
Archives: |
|