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  • Create bar charts, pie charts, and line graphs
  • Create calculated fields with conditional logic.
  • Create dynamic dashboards combining multiple worksheets.
  • Combine multiple data sources using joins, blends, unions, and relationships.
  • Learn various Analytical capabilities of Tableau such as Forecasting, Reference Lines, Clustering etc.
  • Learn everything about Level of Detail Expressions
  • End to End learning on Tableau

Tableau is the solution that thousands of companies use today as they struggle with their big data issues. Working with Tableau isn't just lucrative - it's fun! And unlike most data analysis tools, Tableau uses a drag-and-drop interface, so you don't need to be a programmer to learn Tableau.

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Learn and Apply Fundamental Skills

Get a step-by-step walk-through of the fundamentals of data visualization and data discovery with Tableau. You'll learn how to:

  • Sort, filter, and group your data

  • Create tables, bar charts, line charts

  • Show location using geographic maps

  • Aggregate with sum, average, min, max, and counts

  • Create new fields using calculations

  • Combine data using joins, blends, unions, and relationships.

You'll learn all of the features in Tableau that allow you to explore, experiment with, fix, prepare, and present data easily, quickly, and beautifully.

Contents and Overview

This course begins with Tableau basics. You will navigate the software, connect it to a data file, and export a worksheet, so even beginners will feel completely at ease.

To be able to find trends in your data and make accurate forecasts, you'll learn how to work with data extracts and timeseries.

Also, to make data easier to digest, you'll tackle how to use aggregations to summarize information. You will also use granularity to ensure accurate calculations.

In order to begin visualizing data, you'll cover how to create various charts, maps, scatterplots, and interactive dashboards for each of your projects.

You'll even learn when it's best to join or blend data in order to work with and present information from multiple sources
By the time you complete this course, you'll be a highly proficient Tableau user. You will be using your skills as a data scientist to extract knowledge from data so you can analyze and visualize complex questions with ease.

  • You'll be fully prepared to collect, examine, and present data for any purpose, whether you're working with scientific data or you want to make forecasts about buying trends to increase profits.

Who this course is for:

  • This Tableau course is meant for those who are looking to move forward in their career by building skills in data science and data visualization.
  • Students who wish to prepare for the Tableau Certified Associate certification exam.
  • Candidates who wish to learn Tableau and begin their journey as a Data Analyst

  • Familiarity with Excel is helpful, but not required.
  • You should have access to a computer running Mac or Windows.
  • This Tableau course is meant for those who are looking to move forward in their career by building skills in data science and data visualization.
  • Students who wish to prepare for the Tableau Certified Associate certification exam.
  • Candidates who wish to learn Tableau and begin their journey as a Data Analyst
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  • Section 1 : Welcome to The Course 1 Lectures 00:01:40

    • Lecture 1 :
  • Section 2 : What is Data Visualization 1 Lectures 00:12:04

    • Lecture 1 :
    • What is Data Visualization
  • Section 3 : BI Process 1 Lectures 00:06:17

    • Lecture 1 :
    • BI Process
  • Section 4 : Tableau and It's Architecture 5 Lectures 00:23:33

    • Lecture 1 :
    • What is Tableau ?
    • Lecture 2 :
    • Features of Tableau
    • Lecture 3 :
    • Tableau Vs Power BI
    • Lecture 4 :
    • Tableau Architecture
    • Lecture 5 :
    • How to use Tableau
  • Section 5 : Tableau Desktop 1 Lectures 00:08:07

    • Lecture 1 :
    • Tableau Desktop
  • Section 6 : Relationships, Joins & Unions 1 Lectures 00:00:01

    • Lecture 1 :
    • Relationships, Joins & Unions
  • Section 7 : Sets in Tableau 1 Lectures 00:13:36

    • Lecture 1 :
    • Sets in Tableau
  • Section 8 : Groups in Tableau 1 Lectures 00:13:45

    • Lecture 1 :
    • Groups in Tableau
  • Section 9 : Hierarchies in Tableau 1 Lectures 00:10:04

    • Lecture 1 :
    • Hierarchies in Tableau
  • Section 10 : Filters in Tableau 1 Lectures 00:00:01

    • Lecture 1 :
    • Filters in Tableau
  • Section 11 : Highlighting 1 Lectures 00:10:49

    • Lecture 1 :
    • Highlighting
  • Section 12 : Device Deisgner 1 Lectures 00:14:13

    • Lecture 1 :
    • Device Deisgner
  • Section 13 : Parameters 1 Lectures 00:12:35

    • Lecture 1 :
    • Parameters
  • Section 14 : Data Blending & Mark Size 1 Lectures 00:14:51

    • Lecture 1 :
    • Data Blending & Mark Size
  • Section 15 : Transparency 1 Lectures 00:00:01

    • Lecture 1 :
    • Transparency
  • Section 16 : Date Aggregation 1 Lectures 00:13:04

    • Lecture 1 :
    • Date Aggregation
  • Section 17 : Generated Fields 1 Lectures 00:13:18

    • Lecture 1 :
    • Generated Fields
  • Section 18 : Discrete vs Continuous 1 Lectures 00:14:28

    • Lecture 1 :
    • Discrete vs Continuous
  • Section 19 : Charts in Tableau 1 Lectures 00:00:01

    • Lecture 1 :
    • Charts in Tableau
  • Section 20 : Pivot Tables in Tableau 1 Lectures 00:11:31

    • Lecture 1 :
    • Pivot Tables in Tableau
  • Section 21 : LOD Expressions 1 Lectures 00:00:01

    • Lecture 1 :
    • LOD Expressions
  • Section 22 : Calculated Fields 1 Lectures 00:00:01

    • Lecture 1 :
    • Calculated Fields
  • Section 23 : Formatting 1 Lectures 00:00:01

    • Lecture 1 :
    • Formatting
  • Section 24 : Analytics in Tableau 2 Lectures 00:15:41

    • Lecture 1 :
    • Analytics in Tableau
    • Lecture 2 :
    • Forecasting in Tableau
  • Section 25 : Dashboarding 1 Lectures 00:00:01

    • Lecture 1 :
    • Dashboarding
  • Section 26 : Live Project 1 Lectures

    • Lecture 1 :
    • HR Analytics Dashboard
  • Section 27 : Bonus 1 Lectures

    • Lecture 1 :
    • Interview Guide!!
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2 Courses

A Data Scientist with a passion for turning data into actionable insights, and meaningful stories. Right from the data extraction till the final data product or actionable insights, I enjoy the journey with the data. 10+ years experience working in Data Analytics and Data Sciences across different industry verticals including telecom, cyber security, insurance, e-commerce etc. Conducted various training sessions on Data Science, Analytics, ML & AI, as well as attended various International conferences as keynote speaker & guest on Data Science, ML & AI in various universities across APAC Region. Over 6+ years of training & teaching experience into Data Science & Analytics
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