Complete Introduction to Data Analytics with Tableau
I’ve created a Udemy course which covers a Complete Introduction to Data Analytics with Tableau. This course is the bootcamp of bootcamps!
We’re going to work on 5 projects with 5 different dashboards!
This course will teach you how to interpret project briefs into real, practical dashboards using Tableau. It is ideal if you want to start a career in Data Analytics or want to up-skill yourself.
The Complete Introduction to Data Analytics with Tableau
Kickstart your Data Analytics Career with Tableau by solving Realistic Analytics Projects. Learn Data Visualisation!
Each of these projects will teach you how to work with different data sources such as live Google Sheets, excel spreadsheets and you’ll even get to connect to a cloud data warehouse!
The Data Sources
Project 1: Discount Mart (Sales and Profit Analytics)
Discount Mart is a small supermarket owned by Grant Frost. He wants a dashboard where he can track how well Discount Mart is doing for this year (in terms of Sales, Profit and Quantity Sold).
He would also like to know how well categories are performing as well as different regions.
Grant Frost assumes that most customers buy 2 or more products per basket/order but would like this confirmed by the data.
Grant also noted that Profit is 30% of the selling price.
Dataset: Click here for the .csv datasource
Logo: Click here for the logo
Project 2: Green Destinations (HR Analytics)
Green Destinations is a well known travel agency. The HR Director has recently noticed an increase in employees leaving (attrition). She would like to figure out any trends or patterns. She has surveyed the staff of Green Destinations and provided you with the data.
She would like to know what the attrition rate is (% of people who have left).
She would also like to know if factors like age, years at the company and income play a part in determining if people will leave or not.
Dataset: Click here for the .csv datasource
Logo: Click here for the logo
Project (Extra): MyPaper (Accounts Receivable)
MyPaper is a paper supplier. The company supplies paper locally to businesses. They allow customers to buy paper upfront but also have a credit option. This is where they supply customers with paper, and the customer doesn’t pay an amount upfront but will make frequent smaller payments.
MyPaper wants to do a full recon of their accounts receivable. The Finance manager would like to select a customer and view some details like
Amount the customer has paid each month
Average Days Overdue (on average, how many days is the customer late by?)
List of invoices and amounts by the customer
Number of times the customer has disputed invoiced.
Datasets and Logos:
Dataset: (click the following links for the datasets)
Account Payments for MyPaper.xlsx
Customers for MyPaper.xlsx
Logo: Click Here for the Logo
Project 3: Superstore (Sales Agent Tracker)
Superstore is a famous retailer in Canada. They have expanded into the USA and their business model involves placing Sales Agents in every state in the USA. These sales agents are responsible for bringing in sales for the state that they are assigned.
The Sales Manager wants a dashboard to track how Sales Agents are doing. He wants it to be comparable where he selects a timeframe this year (Example January - March 2020) and he wants sales data for the same period last year. This is so he can track growth.
Additionally, he wants a breakdown of sales per category and subcategory as well as the top performing products.
Dataset: Click here for the zipped folder
Logo: Click here for the logo
Project 4: Northwind Trade (Shipping Analytics)
Northwind Trade is a company which ships a variety of FMCG (Fast Moving Consumer Goods) all over the world.
The Shipping Manager doesn't have much visibility and doesn't know how many orders are processed and shipped on a monthly basis. He would like a dashboard of this where he selects a month and can tell how many orders are outstanding a day and where they should be shipped.
Northwind Trade has a database on Maria DB. The Shipping manager has given us the details to connect to it.
Dataset: The connection details to Maria DB are below.
Server: hostname: relational.fit.cvut.cz
Database:
port: 3306
username: guest
password: relational
Note: If somehow you can’t connect to Maria DB. I’ve added the compressed folder of the database here. Download it and connect to this instead.
Logo: Click here for the logo
Project 5: Tesla (Stock Price Analytics)
Tesla is an American electric vehicle and clean energy company. An important shareholder is tired of receiving only monthly updates of the stock price.
He says that he would like to see any trends of the stock price specifically for the last 3 months. He also wants this data to be updated daily.
He says it's important for him to know the average monthly stock price, daily closing figures and volume of stock traded.
Dataset: We will create a live google sheet!
Logo: Click here for the logo
