This document provides an overview of data types in Tableau including string, number, date, date and time, boolean, and geographic values. It describes how to connect to data in Tableau by selecting a file or server data source. It also discusses changing the data type of fields from the data pane or in a view and explains that dimensions contain qualitative values that affect detail level while measures contain quantitative values that can be aggregated. Finally, it lists some portals for finding open data sets.

2. String values
Number (Integer) values
Date values
Date & Time values
Boolean values
Geographic values
Data types:

3. Connect to data in tableau
On opening Tableau, you will get the start page showing various data sources. Under the header “Connect”,
you have options to choose a file or server or saved data source.
Under Files, choose excel.
Then navigate to the file “Sample – Superstore.xls” as mentioned above.
The excel file has three sheets named Orders, People and Returns. Choose Orders.

5. Changing data type of a field in Data Source page

6. Changing data type of a field from Data pane

7. Changing the data type of a field in the View

8. Dimensions and Measures, Blue and Green
● Dimensions contain qualitative values (such as names, dates, or geographical data). You can use
dimensions to categorize, segment, and reveal the details in your data. Dimensions affect the level of
detail in the view.
● Measures contain numeric, quantitative values that you can measure. Measures can be aggregated.
When you drag a measure into the view, Tableau applies an aggregation to that measure (by
default).

9. Assignment 1 - Superstore Sales Dashboard
Due Date - 27 September 2021
Objective:
To identify the number of customers, in the province region .
To analyse the number of sales, product-wise Identify the number of packages by various ship-mode
and priority province-wise.
To Analyse the various modes of transport used in the superstore.
The display the priority of the order including customers Name by Order ID for taking the further
action.
Derive one meaningful insight on your own.

10. ● data.world
● Data is Plural
● UN Data
● Data.gov
● Kaggle
● NOAA
● Reddit
● World Fact Book
● UN Environmental Data Explorer
● World Health Organization
● Pitney Bowes
Portals For Data: