Tableau — Data Visualization

Published in

YavarTechWorks

3 min readJan 24, 2023

When you talk about Data Visualization, the first word that comes to your mind is — Tableau. I am guessing that’s why you might be here reading this.

This is my first blog in Tableau where you will learn where to start and how to start with Tableau.

Firstly,

What is Tableau?

Tableau is one of the top business intelligence and analytics tools as confirmed by none other than Gartner.

The success story of the tableau is really inspirational. It is extensively used by organizations to make sense of data in a visually insightful format.

Tableau can work with any kind of data be it structured, unstructured or semi-structured. Also, Tableau can connect with many other tools, platforms like Hadoop, R programming, and so on.

Why Tableau?

Does not require any coding knowledge
Easily Shareable
Secure servers
Multiple data sources
easy to create dashboards

Importance of data visualization

Data visualization allows data scientists to effectively convey the outcome of data analysis to the end-users, which enables them to identify the hidden patterns in the data.

It also helps the decision-makers comprehend the exact situation and performance of the business, they can make better decisions.

Data Visualization tools:

Why you should learn Tableau?

Data visualization and predictive analytics is a norm in every industry today
Tableau can work with any data warehousing and ETL tool making it highly versatile
Tableau is constantly updating making the future for a career in Tableau highly promising
Tableau has a big growing community thus making it easy to learn Tableau and excel
You don’t need any specialized skills or programming languages for learning Tableau.

Difference between Tableau Desktop Vs Tableau Public :

Tableau Desktop:

paid
private server
DB connectivity options
unlimited rows of data
real-time refresh

Tableau Public:

free
public server
approx. 1 million rows of data

Datatypes in Tableau:

Now the data types we are dealing with is broadly classified into 2 categories . They are :

Dimensions
Measures

It is very difficult to talk about dimensions and measures without talking about continuous and discrete fields (also known as green and blue). That is because dimensions are typically discrete blue fields, and measures are typically continuous green fields. But using colors to explain the difference between dimensions and measures can cloud one’s understanding of the latter. So here is my attempt at explaining dimensions and measures without mentioning continuous and discrete fields (starting now!).

When you connect to a data source, Tableau automatically assigns each field in the data source as a dimension or a measure. You can find these in the data pane which is split into two sections: dimensions at the top, and measures at the bottom. A faint gray line separates D’s from M’s (see Figure 1).