About the Course:
As companies embrace Data Analytics to improve their awareness, insights and ability to predict trends and provide smarter products and services, Data Analysis is becoming a valuable side skill for just about any role. This course will help professionals in any industry and role to elevate their understanding of data, cleaning data and obtaining insights from various sources of data quickly. Importantly, this course does not aim to teach programming in Python, R, or any other computer language – it is designed for those who are not technically minded and whose role does not require the deeper, more technical work that uses coding.

This course provides a solid foundation of the key concepts of data analysis, as well as practical skills to perform analysis in three popular desktop applications for light data analysis: Excel, Power BI, and Tableau. After completing this course, you will have a good understanding of the problems companies face when capturing, gathering and collating data, as well as the resources to perform practical light analysis and data visualisations in popular desktop applications designed for this task. No coding is required.

Learning Outcomes:
By the end of this course, learners will be able to:
● Identify common issues with data, and rectify simple problems such as wrong data types and missing data
● Apply basic statistical concepts to derive insights from everyday data tasks
● Use Microsoft Excel to perform simple data cleanup, dashboard and data visualisation tasks
● Use Tableau, Power BI to perform simple data cleanup, visualisations and dashboards

Entry Requirements:
Experience in entering, handling, compiling or reporting any type of data is beneficial, but not required. However, learners should be able to create, open, and save Microsoft Excel files, have some basic Excel data input experience and understand the “column, row, cell” arrangement of an Excel spreadsheet.
The course will be of most benefit to those who are manipulating long lists of information of any kind as part of their role and need to obtain reports, visually represent data and gain better insights out of the information they handle. As part of the course, learners are expected to install other software applications if they are not already installed.

Resource Requirements:
Learners must be able to install new trial version software on their computers, or alternatively, should already hold licenses of Excel, Tableau and PowerBI. Trial versions can be uninstalled after completing the course. A student license of Tableau will be available through UCD Professional Academy for all learners participating on this course.  It is preferred for learners to have a Windows computer as there is no Mac version of Power BI available. If learners do not have a Windows machine to work with, they won’t be able to install, use, or complete the final assignment with Power BI. Mac users will, however, still be able to complete the final assignment with Tableau, but that is the only option available. The final assignment can be completed with either Power BI or Tableau.
Professional Academy Diploma in Data Analysis without Coding.

Course Structure:
● Live Online Part-time: One evening per week; 6:30pm to 9:30pm for 12 weeks

 

Course Breakdown:

Module	Overview	Topics/Area Covered
1. Everyday Data Analysis	Introduces the fundamental role that data plays in decision-making, problem-solving, and innovation across industries. How data can be transformed into valuable insights through analytics, and how these insights can be used to improve business performance and drive strategic decisions.	●       Importance of data ●       How data is used for analytics ●       What to expect: results you can achieve at the end of the course ●       Data analysis workflow ●       Roles within data
2. Data Fundamentals	Learn about the different types and sources of data and the various formats in which data can be stored. Learn about data pipelines that allow you to collect, process, and transform data from different sources into a usable format. Understand the data preparation process, which includes cleaning, filtering, and transforming data to ensure it is accurate and consistent.   You will also learn about data exploration techniques, such as data profiling, statistical analysis, and data visualisation, which help you gain insights and identify patterns in the data.	●       Data sources and types ●       Data pipelines ●       Data preparation ●       Data exploration ●       Understanding visualisations and chart types
3. Excel Fundamentals	Learn how to use various Excel functions to manipulate and analyse data efficiently. The class will emphasise the importance of using the correct data types when working with Excel functions to ensure accurate results. Learn how to clean data in Excel to eliminate errors and inconsistencies, as well as how to sort and filter data to focus on specific data subsets.   PivotTables will also be introduced, which are powerful tools that allow students to summarise and analyse large data sets to extract useful insights and trends from the data.	●       Importance of data types ●       Excel functions and formatting ●       Cleaning data in Excel ●       Sorting and filtering data ●       PivotTables

 

4. Excel Statistical Analysis	Learn how to apply statistical functions like mean, median, and standard deviation to different data sets to draw meaningful conclusions. The class will also cover data visualisation techniques, where students will learn how to create charts, graphs, and other visual aids to represent data effectively. A case study will be provided to demonstrate how statistical functions and data visualisation can be used in real-world scenarios.   The unit will also focus on how to derive insights and make data-driven decisions based on the analysis of the data.	●       Statistical functions ●       Data visualisation ●       Case study ●       Insights and decision-making
5. Excel Workshop	Preparation for the assignment, and setting up software packages.	●          Excel Workshop ●          Setting up Tableau ●          Setting up Power BI
6. Power BI- Getting Started	An introduction to Power BI – its interface, functions, Power Query Editor which is where you clean the data, and its ability to visualise data	●       Understanding Power BI and its capabilities ●       Navigating the Power BI interface ●       Transforming data using Power Query Editor ●       Creating a simple report and visualisations
7. Power BI- Intermediate	Introduce calculated columns and measures. Calculated columns and measures in Power BI are similar to functions in Excel in that they both enable users to perform calculations and manipulate data within their respective tools. Just as Excel functions allow users to perform calculations on data within a spreadsheet, calculated columns and measures in Power BI allow users to perform calculations on data within a data model.   These calculations will then be used to build more advanced visualisations that contain deeper insights.	●       Creating calculated columns and measures ●       Working with relationships between tables ●       Building more advanced visualisations
8. Power BI: Case Study	Use the skills and knowledge from previous units to build a comprehensive dashboard from start to finish. This will be a team effort that is guided by the lecturer.	●       Power BI Case Study ●       Building end-to-end dashboard ●       Troubleshooting

 

9. Introduction to Tableau	An introduction to Tableau – its interface and functions. Where you clean and visualise the data.	●                    Introduction to Tableau and its uses in data visualisation ●                    Understanding the Tableau interface and its various components ●                    Data preparation in Tableau ●                    Creating basic visualisations using Tableau
10. Creating Dashboards in Tableau	Introduction to how to manipulate data in Tableau in order to identify patterns. Using multiple sources of data and creating rich visualisations that reveal deep insights.	●                    Introduction to basic calculations and filtering in Tableau ●                    Combining data from multiple sources and blending data in Tableau ●                    Advanced chart types and filtering in Tableau
11. Tableau: Case Study	Use the skills and knowledge from previous units to build a comprehensive dashboard from start to finish. This will be a team effort that is guided by the lecturer	●                    Tableau Case Study ●                    Building end-to-end dashboard in Tableau ●                    Troubleshooting
12. Data Communication	The focus of this unit is purely on using data as a tool for positive change by learning how to report insights in the most effective way.	●       Storytelling with data ●       Best practices for visualisation ●       Activity – Build an “effective” report

 

Course Assessment:

 

Assessed Component	Weighting	Deadline
Assessment One: Excel Project	40%	Week 6
Assessment Two: Final Project	60%	Two weeks after the final lecture

 

Learners will complete two assignments using datasets of their choice to solve practical problems or reveal insights in the data. The two projects should contain elements of data cleaning and visualisation, along with written reports on how the tasks were planned, implemented, and the justification for choices made, etc.

 

Assessment one is an exploratory assignment that requires the learner to select a dataset of their choice and perform an analysis using Excel.

 

Assignment two is also exploratory, and can be completed in either Power BI or Tableau.