# Personal Career & Learning Guide for Data Analyst, Data Engineer and Data Scientist

Dates can play a significant role in data analysis, and understanding how to work with dates in Tableau is an important skill for data analysts. Tableau provides a range of features to help you work with dates, including date calculations, which allow you to perform calculations on dates in your data. In this article, we will take a closer look at Tableau date calculations and how they can be used by data analysts to make better decisions.

Tableau date calculations allow you to perform a wide range of calculations on dates in your data, including determining the difference between two dates, calculating the number of days, weeks, months, or years between two dates, and calculating the date for a specified number of days, weeks, months, or years in the future or past.

One of the key benefits of Tableau date calculations is that they allow you to quickly and easily identify trends and patterns in your data that are based on date ranges. For example, you may want to see the number of sales for each month over the last year, or the average sales for each week over the last six months. With Tableau date calculations, you can easily perform these calculations and include the results in your visualization, so that you can quickly identify trends and patterns in your data.

Another benefit of Tableau date calculations is that they allow you to perform calculations that are not possible with traditional aggregations. For example, you may want to calculate the number of days between a customer’s first purchase and their most recent purchase, or the number of weeks between two dates. With Tableau date calculations, you can easily perform these calculations and include the results in your visualization, so that you can make better decisions based on your data.

In addition to the benefits of Tableau date calculations, they are also easy to use, even for those with little to no experience with data analysis. Tableau’s intuitive interface and straightforward date calculation options make it easy to get started, so that you can quickly start working with your data and making better decisions based on your data.

In conclusion, Tableau date calculations are a powerful and versatile tool for data analysts looking to work with dates in their data. Whether you need to perform calculations based on date ranges, such as number of sales for each month over the last year, or perform calculations that are not possible with traditional aggregations, Tableau date calculations make it easy to get the information you need, so that you can make better decisions based on your data. With its intuitive interface and powerful date calculation capabilities, Tableau is the perfect tool for data analysts looking to get the most out of their data.

# Tableau for Data Analyst – Tableau Date Calculations

Taking too long?

| Open in new tab

# Personal Career & Learning Guide for Data Analyst, Data Engineer and Data Scientist

## Applied Machine Learning & Data Science Projects and Coding Recipes for Beginners

A list of FREE programming examples together with eTutorials & eBooks @ SETScholars

# Projects and Coding Recipes, eTutorials and eBooks: The best All-in-One resources for Data Analyst, Data Scientist, Machine Learning Engineer and Software Developer

Topics included: Classification, Clustering, Regression, Forecasting, Algorithms, Data Structures, Data Analytics & Data Science, Deep Learning, Machine Learning, Programming Languages and Software Tools & Packages.
(Discount is valid for limited time only)

Disclaimer: The information and code presented within this recipe/tutorial is only for educational and coaching purposes for beginners and developers. Anyone can practice and apply the recipe/tutorial presented here, but the reader is taking full responsibility for his/her actions. The author (content curator) of this recipe (code / program) has made every effort to ensure the accuracy of the information was correct at time of publication. The author (content curator) does not assume and hereby disclaims any liability to any party for any loss, damage, or disruption caused by errors or omissions, whether such errors or omissions result from accident, negligence, or any other cause. The information presented here could also be found in public knowledge domains.

# Learn by Coding: v-Tutorials on Applied Machine Learning and Data Science for Beginners

Please do not waste your valuable time by watching videos, rather use end-to-end (Python and R) recipes from Professional Data Scientists to practice coding, and land the most demandable jobs in the fields of Predictive analytics & AI (Machine Learning and Data Science).

The objective is to guide the developers & analysts to “Learn how to Code” for Applied AI using end-to-end coding solutions, and unlock the world of opportunities!