Data is an integral part of every successful business, as companies increasingly make data-driven decisions. According to IBM, there were more than 2.7 million data jobs in 2020.
In the Data Analyst Accelerator, you will learn to use data analysis tools, make data-driven decisions to improve business performance, and learn to create data visualizations. No prerequisites or previous experience required to sign up!
Lesson: What is a Data Analyst, how do they use data, and what does a day in the life of a Data Analyst look like?
Task: Reflection on current skills and skills to develop to be a Data Analyst.
Lesson: What tools to Data Analysts use? How do each of these help Data Analysts?
Task: 1) Quiz on which tool is most useful for each task. 2) Get excel and tableau
Lesson: How to ask questions - Framing the problem, and using the 5 Whys approach to Root Cause Analysis.
Task: Case study given to students with a business problem. Frame the problem and begin with the 5 whys approach
Lesson: Determining clients needs and the right data for the right problem.
Task: More information on the business given. Determine what data should be collected and how it should be presented.
Lesson: Creating and communicating a plan of action
Task: Write a project brief outlining the next steps for your client.
Lesson: Data comes from multiple sources. How to aggregate data
Task: Gather data from different sources and extract to Excel
Lesson: Importance of cleaning data, removing unnecessary data, and common techniques
Task: Normalise and standardise the data compiled on excel.
Lesson: Pivot Tables and Chart usage in Excel, how to create
Task: Create a Pivot Table and Chart for your case study
Lesson: Using Tableau to create dashboards and visualise data
Task: Connect excel to Tableau, and build a dashboard for your case study.
Lesson: Identifying your narrative and creating a story that is easy to follow with your data
Task: Create a report with your visualisations from Excel and Tableau to tell a story with your data.
Lesson: Finding a dataset that interests you and framing the problem when it is not clearly defined.
Task: Define the question and need for analysis
Task: Collecting data from sources, cleaning through unnecessary data
Task: Visualise data with the tool
Lesson: How to create a compelling presentation with your findings
Task: Create a final presentation with your findings.