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Tableau For Data Science: From Zero To Hero

Tableau For Data Science: From Zero To  Hero


Published 11/2024
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz
Language: English | Size: 2.83 GB | Duration: 10h 26m


Transform raw data into insights with step-by-step Tableau training for beginners—start your path to becoming a pro!


What you'll learn
Recognize Tableau interface components, such as worksheets, shelves, and cards, and explain how to use various Tableau tools like filters, sorting & grouping
Develop effective data visualizations that incorporate design principles such as layout, color & labeling, to effectively communicate insights to the audience
Create charts
Work with Timeseries Data
Understand Continuous and Discrete Data
Assigning Geographical Roles to Data Elements
Work with Parameters
Connect to Various Data Sources
Combine Data with Joins and Blends
Build Advanced Visualization
Apply Level of Detail (LOD) Calculations
Create Interactive Dashboards
Use Table Calculations
Adding Filters and Quick Filters
Adding Actions to Dashboards (filters & highlighting)
Requirements
Basic knowledge of computers
A PC with a working internet connection
Interest in Data Visualization
Description
Ready to transform raw data into powerful insights? With Tableau for Data Science: Zero to Hero, you'll quickly go from beginner to pro in data visualization. This course is perfect for anyone looking to create stunning, insightful dashboards that truly make data come to life.Starting with the basics, you'll learn one of Tableau's essential concepts: the difference between continuous and discrete data (those famous green and blue pills!) and why it matters. From there, we'll dive into connecting data sources like Excel, Google Sheets, and databases, so you'll always have the tools to work with any data. And don't worry—no prior experience is required; we cover everything step-by-step!This course goes beyond simple charts. You'll master various visualization types (like bar charts, area charts, scatter plots) and explore advanced Tableau features like Level of Detail (LOD) calculations, table calculations, and dynamic parameters. Imagine being able to create data-driven dashboards that capture and communicate trends, patterns, and insights in seconds.What makes this course unique is our focus on practical skills you can apply immediately. From creating heatmaps and interactive maps to setting up actions that make your dashboards interactive, you'll gain the skills to make data sing. And with each lesson, you'll feel more empowered to design dashboards that engage users and make complex data accessible and easy to understand.What You Will Learn:Understand continuous vs. discrete data and use it effectively in TableauConnect to and blend multiple data sources with easeCreate impactful visualizations like dual-axis charts, Gantt charts, and moreBuild advanced Tableau calculations and LOD expressions to deepen insightsDesign polished, interactive dashboards with user-friendly layouts and filtersJumpstart your Tableau journey and turn raw data into decisions. Join Tableau for Data Science: Zero to Hero today and get ready to become the Tableau expert your team needs!
Overview
Section 1: Introduction
Lecture 1 Introduction
Lecture 2 IMPORTANT: What you should know
Lecture 3 Tableau Files Types
Lecture 4 About Exercise Files
Lecture 5 Tableau Interface
Lecture 6 Order of operations in Tableau
Lecture 7 About the Course Project
Section 2: Fields
Lecture 8 Green and Blue fields
Lecture 9 How do green and blue fields impact rows and columns?
Lecture 10 How do green and blue fields influence filters?
Lecture 11 How do green and blue fields impact colors?
Lecture 12 How do green and blue fields influence dates?
Lecture 13 Exercise 1
Lecture 14 Exercise 1: Solution
Section 3: Connect to a Data Source
Lecture 15 Connect to Excel Sheets
Lecture 16 Clean Excel data with the data interpreter
Lecture 17 Connect to Google Sheets
Lecture 18 Connecting to PDF files
Lecture 19 Setting default properties
Lecture 20 Saving your data sources for later use
Lecture 21 Exercise 2
Lecture 22 Exercise 2 - Solution
Section 4: Combining Data
Lecture 23 Combining data using relationships
Lecture 24 Types of joins in data
Lecture 25 Join tables on the same data connection
Lecture 26 Joining tables from two different databases using a cross-database join
Lecture 27 Appending one data source to another using unions
Lecture 28 Exercise 3 (Part 1)
Lecture 29 Exercise 3 (Part 1) - Solution
Lecture 30 Exercise 3 (Part 2)
Lecture 31 Exercise 3 (Part 2) - Solution
Section 5: When and How to Generate Data Extracts
Lecture 32 Pros and cons of using a data extract
Lecture 33 Create a data extract
Lecture 34 Limiting data in a data extract
Lecture 35 Edit a data extract to include more data
Section 6: Comparing Measures
Lecture 36 Measure Names and Measure Values
Lecture 37 Combined axis chart
Lecture 38 Dual axis chart
Lecture 39 Bar-in-bar chart
Lecture 40 Multiple measure crosstab
Lecture 41 Scatter plot
Lecture 42 Exercise 4 (Part 1)
Lecture 43 Exercise 4 (Part 1) - Solution
Lecture 44 Exercise 4 (Part 2)
Lecture 45 Exercise 4 (Part 2) - Solution
Section 7: Transform Your Data with Calculations
Lecture 46 Calculations in Tableau
Lecture 47 The order of operations in the calculation
Lecture 48 String functions
Lecture 49 Date functions
Lecture 50 Logic functions
Lecture 51 Table calculations
Lecture 52 Direction and scope of table calculations
Lecture 53 Level of Detail (LOD) Calculations
Lecture 54 EXCLUDE LOD calculations
Lecture 55 INCLUDE LOD calculations
Lecture 56 FIXED LOD calculations
Lecture 57 Calculations in a Join
Lecture 58 Exercise 5
Lecture 59 Exercise 5- Solution
Section 8: Mapping Your Data
Lecture 60 About creating maps in Tableau
Lecture 61 Creating filled maps
Lecture 62 Symbol maps
Lecture 63 Customizing your maps
Lecture 64 Create locations from coordinates
Lecture 65 Create lines to connect locations on a map
Lecture 66 Analyzing distances through buffer calculations
Lecture 67 Analyzing spatial data through intersection calculations
Lecture 68 Exercise 6
Lecture 69 Exercise 6- Solution
Section 9: The Analytics Tab
Lecture 70 The Analytics pane
Lecture 71 Constant reference line
Lecture 72 Dynamic average reference line
Lecture 73 Box plots
Lecture 74 Adding totals and sub-totals to a view
Lecture 75 Adding a forecast to a view
Lecture 76 Adding a trend line to a view
Lecture 77 Data clusters in a view
Lecture 78 Reference band
Lecture 79 Exercise 7 (Part 1)
Lecture 80 Exercise 7 (Part 1) - Solution
Lecture 81 Exercise 7 (Part 2)
Lecture 82 Exercise 7 (Part 2) - Solution
Section 10: Using Parameters for Viewer Input
Lecture 83 How do parameters differ from filters?
Lecture 84 Using parameters in a calculation
Lecture 85 Dynamic reference lines using parameters
Lecture 86 Use a parameter to select dimensions and measures
Lecture 87 Use a parameter to search free text fields
Lecture 88 Top N analysis
Lecture 89 Dynamic parameters
Lecture 90 Exercise 8
Lecture 91 Exercise 8- Solution
Section 11: Dashboard and Design Tips
Lecture 92 The dashboard's user interface
Lecture 93 Tiled dashboard
Lecture 94 Floating dashboard
Lecture 95 Filter Actions in Dashboards
Lecture 96 Highlight Actions
Lecture 97 URL actions
Lecture 98 Navigate between panels
Lecture 99 Set actions
Lecture 100 Containers
Lecture 101 Exercise 9
Lecture 102 Exercise 9- Solution (1/2)
Lecture 103 Exercise 9- Solution (2/2)
Section 12: Analysis Tips and Tricks
Lecture 104 Bar charts
Lecture 105 Use colors to highlight data
Lecture 106 Timelines
Lecture 107 Small multiple timelines
Lecture 108 Month-over-month or year-over-year charts
Lecture 109 Combined axis bar chart
Lecture 110 Combined axis timeline
Lecture 111 Dual axis timeline
Lecture 112 Crosstab
Lecture 113 Add color to a crosstab to create a highlight table.
Lecture 114 Turning a crosstab into a heatmap
Lecture 115 Area chart
Lecture 116 Line charts vs. Area charts
Lecture 117 100% Area Charts
Lecture 118 Stacked bar charts
Lecture 119 100% stacked bar chart
Lecture 120 Add a running total to a line chart
Lecture 121 Difference between values in a line chart
Lecture 122 Scatter plot and bubble chart
Lecture 123 Creating a connected scatterplot to display changes over time
Lecture 124 Bar-in-bar chart and Candlestick chart
Lecture 125 Symbol map
Lecture 126 Filled area map
Lecture 127 Pie charts
Lecture 128 Gantt charts
Aspiring Data Scientists,Data Analysts,Business Intelligence Professionals,Students & Beginners,Entrepreneurs and Small Business Owners,You should take this course if want to learn Tableau completely from scratch
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Tableau For Data Science: From Zero To  Hero


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