54 Days Of Tableau Complete Masterclass

Learn all Tableau aspects from Basic to Advanced and understand best visualisation principles

[b]What you'll learn[/b]

Learn how to solve Real-Life Business, Industry and World challenges using Tableau

How and when to use different chart types such as Heatmaps, Bullet Graphs, Bar-in-bar charts, Dual Axis Charts and more!

Tableau fundamentals - Discrete vs Continuous fields, Dimensions vs Measures, Aggregation and Granularity, etc

How to Organize & Simplify your data in Tableau: Computed sort, Manual sort, Hierarchies, Groups vs Sets, Dynamic sets, Static sets, etc

Analytics in Tableau: Reference Lines, Reference Bands, Trend Lines, Instant Analytics, Box Plots, Forecasting, etc

How to do Data Prep in Tableau: Joins, Blends, Unions, Pivots, Wildcards, Merging Mismatched Fields, Using Calculations in Join clauses, etc

Mapping techniques: Layering, Lasso, Radial Selection, Custom Territories, Dual Axis Maps

Calculations: Arithmetic, String & Date Calculations, Logic Statements, Calculations with Parameters, Calculations in a Blend, etc

When & How to use Table Calculations: Percent of Total, Rank, Running Total, Scope & Direction of Table Calculations and more!

Level Of Detail (LOD) Expressions: FIXED, INCLUDE, EXCLUDE, The LOD Planning Technique, ATTR() function, Order of Operations & LODs and more!

Dashboard Actions: Filter / Highlight / Parameter / Set Actions, Worksheet Actions, and more!

Evaluate and improve poorly designed visualizations, simplifying dual-axis charts and other complex visual elements.

Apply advanced table calculations and Level of Detail (LOD) expressions for complex data analysis.

Perform cross-database joins and other advanced data connections to prepare comprehensive datasets.

Solve technical questions related to expert-level Tableau functionalities, including top-end analysis and data blending.

Create interactive dashboards that effectively deliver insights, incorporating multiple views and best practices.

Build compelling data stories that clearly communicate insights, following exam guidelines.

[b]Requirements[/b]

You should have access to Tableau software.

[b]Description[/b]

Starting from scratch or building on existing skills? No matter the skill level, this course builds up your Tableau, visualization, and BI skills to the next level, and supports your growth with one-on-one mentorship with industry experts.This program consists of two stages. First master every aspect of Tableau - charts, groups, sets, LOD expressions, advanced calculations, analytics, maps, dashboards, actions, data transformation techniques and more.Skyrocket your Career by learning Tableau !Tableau is, perhaps, the most powerful & popular tool for data visualization.So. Do you want to become an expert in Tableau ?You've come to the right place.In this course you will learn everything you need to know to learn Tableau from A to Z. You don't need to be an expert to learn the Tableau.This course covers every single topic from the official exam preparation guide:Tableau FundamentalsData ConnectionsOrganizing & Simplifying DataField & Chart TypesCalculationsMappingAnalyticsDashboards.and more!Wait! There's more! - EPIC Datasets!This isn't one of those boring courses with the same dataset that you've seen a Million times before.NO.Hands-On Experience is one of the most important things in Data Science / Business Intelligence / Data Analytics work.In fact, often the Dataset is at least as important as the concept you are learning! Right?!That's why for this course we've specifically curated some of the most exciting datasets you will ever find!Almost every section comes with a New Dataset & a New Challenge.You will GET Hooked By this course!Plus, the datasets come from some of the kick-butt companies! Check this out:SpotifyThe NBARotten TomatoesKaggleWorldBankGlassdoorAirbnb.and more!Not enough awesomeness for you? Enough?Doesn't matter! There's more anyway Smile

With this course you will get TONS of Practice: dozens of mini-challenges, quizzes, homework exercises, exam tips, and additional resources.Best. Tableau. Course. You. Will. Ever. Find. Boom!

Overview

Section 1: Week 1 - Day 1

Lecture 1 Welcome

Lecture 2 Installing Tableau

Lecture 3 Get The Dataset!

Lecture 4 Barchart

Lecture 5 Linechart

Lecture 6 Stacked Bar Chart

Lecture 7 Histograms

Lecture 8 Heatmaps

Section 2: Week 1 - Day 2

Lecture 9 Treemaps - Part 1

Lecture 10 Treemaps - Part 2

Lecture 11 Bullet Graph

Lecture 12 Combined Axis Chart - Part 1

Lecture 13 Combined Axis Chart - Part 2

Lecture 14 Dual Axis Chart

Section 3: Week 1 - Day 3

Lecture 15 Scatterplot - Part 1

Lecture 16 Scatterplot - Part 2

Lecture 17 Cross Tab

Lecture 18 Bar-in-bar Chart !

Lecture 19 Boxplots

Lecture 20 Using Mark Labels and Annotations

Lecture 21 Adding Titles Captions and Tooltips

Lecture 22 Editing Axes

Section 4: Week 1 - Day 4

Lecture 23 Week 1 - Day 4 - Dataset

Lecture 24 Get the Dataset

Lecture 25 How the NBA works (An Amateur's Explanation)

Lecture 26 Navigating Tableau

Lecture 27 Using "Show Me"

Lecture 28 Using Tableau-generated fields

Lecture 29 Discrete vs Continuous Fields | Slides

Lecture 30 Discrete vs Continuous Fields (Practical)

Section 5: Week 1 - Day 5

Lecture 31 Dimensions vs Measures | Slides

Lecture 32 Aggregation and Granularity (Part 1)

Lecture 33 Aggregation and Granularity (Part 2)

Lecture 34 Aggregation and Granularity (Part 3)

Lecture 35 The 4 Roles of Data fields | Slides

Lecture 36 Week 1 Homework Challenge

Lecture 37 Week 1 Homework Solution

Section 6: Week 2 Day 6

Lecture 38 Dimensions (Discrete & Continuous) - Advanced Tutorial

Lecture 39 Measures (Discrete & Continuous) - Advanced Tutorial

Lecture 40 Default Aggregation

Lecture 41 Aggregating Dimensions

Lecture 42 Data Types in Tableau | Slides

Lecture 43 Saving a Tableau Packaged Workbook *.twbx

Lecture 44 Section recap

Section 7: Week 2 - Day 7

Lecture 45 Get the Dataset & Challenge | Connect to the data here as well

Lecture 46 Date is (almost) Always a Dimension

Lecture 47 Discrete vs Continuous Date Fields

Lecture 48 Datepart vs Datetrunc | Slides

Lecture 49 Datepart vs Datetrunc (Practical)

Section 8: Week 2 - Day 8

Lecture 50 Discrete vs Continuous Date Fields (cont.) - Advanced Tutorial | Slides

Lecture 51 Datepart (Discrete & Continuous) - Advanced Tutorial

Lecture 52 Datetrunc (Discrete & Continuous) - Advanced Tutorial

Lecture 53 Can Date be a Measure?

Lecture 54 Section recap | PPT slides, quick

Section 9: Week 2 - Day 9

Lecture 55 Get the Dataset & Challenge

Lecture 56 Filter data - Dimension Filter

Lecture 57 Filter data - Date Filter

Lecture 58 Filter data - Measure Filter

Lecture 59 Filter data - Relevant Values

Lecture 60 Filter data - Top 10

Section 10: Week 2 - Day 10

Lecture 61 Filter data - Context Filter (Part 1)

Lecture 62 Filter data - Context Filter (Part 2)

Lecture 63 Filter data - Context Filter (Part 3)

Lecture 64 Filter data - Context Filter (Part 4)

Lecture 65 Filter data - Scope of Filter

Lecture 66 Add a Parameter - Filters

Lecture 67 Week 2 - Homework Challenge

Lecture 68 Week 2 - Homework Solution

Section 11: Week 3 - Day 11

Lecture 69 Get the Dataset & Challenge

Lecture 70 Sort data - Computed Sort

Lecture 71 Sort data - Manual Sort

Lecture 72 Build Hierarchies

Lecture 73 Build Groups - Visual Group

Lecture 74 Build Groups - Using Labels

Section 12: Week 3 - Day 12

Lecture 75 Week 3 - Homework Challenge

Lecture 76 Week 3 - Homework Solution

Section 13: Week 3 - Day 13

Lecture 77 Build Sets - Static

Lecture 78 Build Sets - Dynamic

Lecture 79 Groups vs Sets

Lecture 80 Build Sets - Combining Sets (Part 1)

Lecture 81 Build Sets - Combining Sets (Part 2)

Lecture 82 Build Sets - Parameter Control

Section 14: Week 3 - Day 14

Lecture 83 Get the Dataset & Challenge

Lecture 84 Reference Lines

Lecture 85 Reference Bands

Lecture 86 Reference Bands - Parameter Control (Part 1)

Lecture 87 Reference Bands - Parameter Control (Part 2)

Lecture 88 Data Highlighter

Lecture 89 Trend Lines

Lecture 90 Trend Model

Lecture 91 Reference Distributions

Lecture 92 Instant Analytics

Section 15: Week 3 - Day 15

Lecture 93 Trend Lines Multiplot (not compulsory for exam)

Lecture 94 Drag & Drop Analytics

Lecture 95 Box Plots

Lecture 96 Extra: Box Plots Theory

Lecture 97 Bins & Histograms

Lecture 98 Forecasting (Part 1)

Lecture 99 Forecasting (Part 2)

Lecture 100 Statistical Summary Card

Section 16: Week 4 - Day 16

Lecture 101 Get the Dataset & Challenge | Connect to the data here as well

Lecture 102 Union

Lecture 103 Union with Wildcard

Lecture 104 Merging Mismatched Fields

Lecture 105 Understanding how LEFT, RIGHT, INNER, and OUTER Joins Work

Lecture 106 Joins with Duplicate Values

Lecture 107 Joining on Multiple Fields

Lecture 108 Single Connection Joins

Lecture 109 Cross-Database (Multiple Connections) Joins

Section 17: Week 4 - Day 17

Lecture 110 Union-Join-Union Challenge

Lecture 111 Using Calculations in Join Clauses

Lecture 112 Blending (Part 1)

Lecture 113 Blending (Part 2)

Lecture 114 Create a Calculated Field in a Blend

Section 18: Week 4 - Day 18

Lecture 115 Section Intro

Lecture 116 Get the Dataset

Lecture 117 Connect to Different Data Source Types

Lecture 118 Pivot

Lecture 119 Data Interpreter

Lecture 120 Automatic & Custom Split

Lecture 121 Managing Data Properties (Names, Aliases, Types, Geographic Roles, Defaults)

Lecture 122 Metadata Grid

Lecture 123 Data Source Filters

Section 19: Week 4 - Day 19

Lecture 124 Filetypes in Tableau | Slides

Lecture 125 Live Connections vs Packaged Workbooks (*.TWB vs *.TWBX)

Lecture 126 Metadata Properties vs Packaged Data Sources (*.TDS vs *.TDSX)

Lecture 127 Tableau Extracts *.HYPER (vs *.TDE) (Part 1)

Lecture 128 Tableau Extracts *.HYPER (vs *.TDE) (Part 2)

Lecture 129 Data Extracts with Multiple Tables

Lecture 130 Extract Limitations

Lecture 131 Section recap | PPT slides, quick

Section 20: Week 4 - Day 20

Lecture 132 Get the Dataset & Challenge | Connect the data here as well

Lecture 133 Modifying locations

Lecture 134 Navigating Maps

Lecture 135 Map Options

Lecture 136 Filtering Maps

Lecture 137 Map Layering

Lecture 138 Geographic Search

Lecture 139 Lasso & Radial Selection

Lecture 140 Week 4 - Homework Challenge

Lecture 141 Week 4 - Homework Solution

Section 21: Week 5 - Day 21

Lecture 142 Custom Territories (Part 1)

Lecture 143 Custom Territories (Part 2)

Lecture 144 Custom Territories (Part 3)

Lecture 145 Custom Territories (Part 4)

Lecture 146 Using Latitude and Longitude coordinates

Lecture 147 Exploring our Map

Lecture 148 Density Plots / Heat Maps

Lecture 149 Dual Axis Map

Section 22: Week 5 - Day 22

Lecture 150 Get the Dataset & Challenge | Connect to the data here as well

Lecture 151 Preparing the worksheets

Lecture 152 Creating the dashboard

Lecture 153 Dashboard Size

Lecture 154 Device Preview & Adding Device Layouts (Part 1)

Lecture 155 Device Preview & Adding Device Layouts (Part 2)

Lecture 156 Auto-generating the Mobile Layout

Lecture 157 Layout menu - Exam trick questions

Section 23: Week 5- Day 23

Lecture 158 Visual best practices for devices

Lecture 159 Working with Hidden Sheets

Lecture 160 Publishing & Sharing options

Lecture 161 Share twbx as an Image

Lecture 162 Share twbx as a PDF

Lecture 163 Building a Story

Section 24: Week 5 - Day 24

Lecture 164 Week 5 Homework Challenge

Lecture 165 Week 5 Homework Solution

Section 25: Week 5 - Day 25

Lecture 166 Get the Dataset & Challenge | Connect to the data here as well

Lecture 167 Exploring the Dataset

Lecture 168 Creating a Map of Kiva Loans (Part 1)

Lecture 169 Creating a Map of Kiva Loans (Part 2)

Lecture 170 Creating a Timeline of Funded Amounts

Lecture 171 Creating a Barchart for Sector

Lecture 172 Creating a Pie Chart of Split by Gender

Lecture 173 Build the Kiva Loans Dashboard

Section 26: Week 6 - Day 26

Lecture 174 Action: Filter

Lecture 175 Action: Highlight

Lecture 176 Action: Change Parameter

Lecture 177 Action: Change Parameter (Exam Insights: Agreggations)

Lecture 178 Action: Change Parameter (Concatenation)

Section 27: Week 6 - Day 27

Lecture 179 Action: Change Set Values (Part 1)

Lecture 180 Action: Change Set Values (Part 2)

Lecture 181 Action: Change Set Values (Exam tips)

Lecture 182 Action: Go to Sheet

Lecture 183 Action: Go to URL

Lecture 184 Worksheet Actions

Lecture 185 Displaying a numeric KPI

Section 28: Week 6 - Day 28

Lecture 186 Get the Dataset & Challenge | Connect to the data here as well

Lecture 187 Creating a Simple Calculated Field

Lecture 188 String Calculated Field

Lecture 189 Date Calculated Field

Lecture 190 Row-Level vs Aggregated Calculations (Part 1)

Lecture 191 Row-Level vs Aggregated Calculations (Part 2)

Lecture 192 Row-Level vs Aggregated Calculations (Part 3)

Section 29: Week 6 - Day 29

Lecture 193 Logic Statements (Part 1)

Lecture 194 Logic Statements (Part 2)

Lecture 195 Working with Parameters (Part 1)

Lecture 196 Working with Parameters (Part 2)

Lecture 197 Calculate Field in Blend (Part 1)

Lecture 198 Calculate Field in Blend (Part 2)

Lecture 199 Totals & Sub-totals

Lecture 200 Ad-Hoc Calculations

Section 30: Week 6 - Day 30

Lecture 201 Week 6 Homework Challenge

Lecture 202 Week 6 - Homework Solution

Lecture 203 Get the Dataset & Challenge | Connect to the data here as well

Lecture 204 Quick Table Calculations: Percent of Total

Lecture 205 Quick Table Calculations: Rank

Lecture 206 Quick Table Calculations: Running Total

Lecture 207 Nested Table Calculations

Lecture 208 Quick Table Calculations: Moving Average

Lecture 209 Quick Table Calculations: Difference

Lecture 210 Quick Table Calculations: Percent Difference

Lecture 211 Table Calculations Theory: Scope and Direction

Section 31: Week 7 - Day 31

Lecture 212 Hands-on practice with Scope of Table Calculations (Part 1)

Lecture 213 Hands-on practice with Scope of Table Calculations (Part 2)

Lecture 214 Hands-on practice with Scope of Table Calculations (Part 3)

Lecture 215 Custom Table Calculations

Lecture 216 Hands-on practice with Direction of Table Calculations (Part 1)

Lecture 217 Hands-on practice with Direction of Table Calculations (Part 2)

Lecture 218 Table Calculations and Order of operations in Tableau

Section 32: Week 7 - Day 32

Lecture 219 Get the Dataset & Challenge | Connect to the data here as well

Lecture 220 Level of Detail (LOD) Expressions Intuition | Slides (fast)

Lecture 221 Use-Case #1: FIXED LOD - Percent total

Lecture 222 LOD Planning

Lecture 223 Building the LOD

Lecture 224 Building the Visualization

Section 33: Week 7 - Day 33

Lecture 225 FIXED LOD - Discussion

Lecture 226 Use-Case #2: INCLUDE LOD - Average of Top Deals by Store

Lecture 227 LOD Planning & Building

Lecture 228 Building the Visualization

Lecture 229 INCLUDE LOD - Discussion

Lecture 230 Use-Case #3: EXCLUDE LOD - Comparative Sales Analysis

Section 34: Week 7 - Day 34

Lecture 231 LOD Planning

Lecture 232 Building the LOD

Lecture 233 Building the Visualization

Lecture 234 Building the Visualization - Add a Parameter

Lecture 235 Building the Visualization - Add Colour

Lecture 236 EXCLUDE LOD - Discussion (Part 1) (ATTR function)

Lecture 237 EXCLUDE LOD - Discussion (Part 2)

Section 35: Week 7 - Day 35

Lecture 238 Use-case #4: Nested LODs

Lecture 239 LOD Planning & Building - LOD A

Lecture 240 LOD Planning & Building - LOD B

Lecture 241 Building the Visualization

Lecture 242 Nested LODs - Discussion (Part 1)

Lecture 243 Nested LODs - Discussion (Part 2)

Lecture 244 Top 15 LOD Expressions

Lecture 245 Week 7 Homework Challenge

Lecture 246 Week 7 Homework Solution Part 1

Lecture 247 Week 7 Homework Solution Part 2

Section 36: Week 8 - Day 36

Lecture 248 Welcome to this part on Table Calculations

Lecture 249 Table Calculations Theory - A Quick Revision

Lecture 250 Course Materials

Section 37: Week 8 - Day 37

Lecture 251 The Challenge: Stock Prices of Car Companies

Lecture 252 Connecting to the Dataset

Lecture 253 The Plan

Lecture 254 Creating an If Statement

Lecture 255 Adding a Table Calculation

Lecture 256 Verifying the Scope of the Table Calculation

Lecture 257 Relative Stock Price Calculation

Lecture 258 Discussion

Lecture 259 Homework Assignment

Lecture 260 Homework Solution (Part 1)

Lecture 261 Homework Solution (Part 2)

Section 38: Week 8 - Day 38

Lecture 262 The Challenge: Kickstarter Projects

Lecture 263 Basic Timeline

Lecture 264 Running Total Table Calculation

Lecture 265 Creating the Common Baseline (Part 1)

Lecture 266 Creating the Common Baseline (Part 2)

Lecture 267 Analysing The Visualization

Lecture 268 Homework Challenge

Lecture 269 Homework Solution

Lecture 270 The Challenge: Kiva Loans Gender Split

Lecture 271 Running Total Table Calculation

Lecture 272 Adding a Secondary Table Calcuation (Percent of Total)

Lecture 273 Discussion (Part 1): Ordinary Percent of Total Comparison

Lecture 274 Discussion (Part 2): Specific Dimensions

Lecture 275 Homework Challenge

Lecture 276 Homework Solution

Section 39: Week 8 - Day 39

Lecture 277 The Challenge: International Soccer Results

Lecture 278 Preparing the Dataset

Lecture 279 Basic Bump Chart

Lecture 280 Advanced Bump Chart

Lecture 281 Dashboard with Highlighting (Part 1)

Lecture 282 Dashboard with Highlighting (Part 2)

Lecture 283 Discussion

Lecture 284 Extra: Home vs Away Matches

Lecture 285 Week 8 - Homework Challenge 4

Lecture 286 Week 8 - Homework Solution 4 (Part 1)

Lecture 287 Week 8 - Homework Solution 4 (Part 2)

Lecture 288 Week 8 - Homework Solution 4 (Part 3)

Lecture 289 Week 8 - Homework Solution 4 (Part 4)

Section 40: Week 9 - Day 40

Lecture 290 The Challenge: World Internet Usage Analysis

Lecture 291 Creating Custom Territories

Lecture 292 Calculated Fields (Part 1): Planning

Lecture 293 Calculated Fields (Part 2): Row-Level Calcuations

Lecture 294 Calculated Fields (Part 3): Aggregate Calculations

Lecture 295 Weighted Average Table Calculation

Lecture 296 Calculating the Priority Score

Lecture 297 Week 9 - Homework Challenge-5

Lecture 298 Week 9 - Homework Solution-5

Section 41: Week 9 Day 41

Lecture 299 The Challenge: Glassdoor Pay Analysis

Lecture 300 Window_Avg Table Calculation

Lecture 301 Logical Statements via Table Calculations

Lecture 302 Discussion

Lecture 303 The Challenge: Tesla Car Sales Analysis

Lecture 304 Data Preparation

Lecture 305 Quick Moving Average

Lecture 306 Parameterized Moving Average

Lecture 307 Independent Axis Ranges

Lecture 308 Week 9 - Homework Challenge-6

Lecture 309 Week 9 - Homework Solution-6 (Part 1)

Lecture 310 Week 9 - Homework Solution-6 (Part 2)

Lecture 311 Week 9 - Homework Solution-6 (Part 3)

Lecture 312 Week 9 - Homework Solution-6 (Part 4)

Lecture 313 Week 9 - Homework Challenge-7

Lecture 314 Week 9 - Homework Solution-7

Section 42: Week 9 Day 42

Lecture 315 The Challenge: Marvel Characters

Lecture 316 New Characters Timeline

Lecture 317 Difference from Global Average

Lecture 318 Difference from Pane Average

Lecture 319 Formatting

Lecture 320 Week 9 - Homework Challenge-8

Lecture 321 Week 9 - Homework Solution-8

Section 43: Week 9 Day 43

Lecture 322 Welcome to this part on LOD Expressions

Lecture 323 LOD Theory - A Quick Revision

Lecture 324 The Challenge: Olympic Medals

Lecture 325 LOD Planning

Lecture 326 Building the LOD

Lecture 327 Building The Visualization

Lecture 328 Rebuilding the LOD

Lecture 329 Discussion

Lecture 330 Week 9 - Homework Challenge-9

Lecture 331 Week 9 - Homework Solution-9

Section 44: Week 9 Day 44

Lecture 332 The Challenge: Returning Customers of an Online Retail Store

Lecture 333 Connecting to the Datasets

Lecture 334 Exploratory Data Analysis (EDA)

Lecture 335 LOD Planning

Lecture 336 Building the LOD

Lecture 337 Building the Visualizations

Lecture 338 Building the Dashboard

Lecture 339 Week 9 - Homework Challenge-10

Lecture 340 Week 9 - Homework Solution-10

Section 45: Week 10 - Day 45

Lecture 341 The Challenge: Analyzing LeBron James' Basketball Career

Lecture 342 LOD Planning

Lecture 343 Building the LOD

Lecture 344 Building The Categories

Lecture 345 Building The Visualization

Lecture 346 Adding Parameter Control

Lecture 347 Discussion

Lecture 348 Week 10 - Homework Challenge-11

Lecture 349 Week 10 - Homework Solution-11 (Part 1)

Lecture 350 Week 10 - Homework Solution-11 (Part 2)

Lecture 351 Week 10 - Homework Solution-11 (Part 3)

Section 46: Week 10 - Day 46

Lecture 352 The Challenge: World Regional GDPs

Lecture 353 LOD Planning

Lecture 354 Building the LOD

Lecture 355 Building the Visualization

Lecture 356 Discussion

Lecture 357 Week 10 - Homework Challenge-12

Lecture 358 Week 10 - Homework Solution-12

Section 47: Week 10 - Day 47

Lecture 359 The Challenge: Analyzing Michael Jordan's Basketball Career

Lecture 360 LOD Planning

Lecture 361 Building The Visualization

Lecture 362 Adding Parameter Control

Lecture 363 Discussion (Part 1)

Lecture 364 Discussion (Part 2)

Lecture 365 Discussion (Part 3)

Lecture 366 Discussion (Part 4)

Section 48: Week 10 - Day 48

Lecture 367 Welcome to this part on Visual Best Practices

Lecture 368 Legal information: Tableau Public Terms of Service

Lecture 369 The Atkinson-Shiffrin Memory Model

Lecture 370 Pre-Attentive Attributes

Lecture 371 Directing Attention with Colour (Part 1)

Lecture 372 Directing Attention with Colour (Part 2)

Lecture 373 Directing Attention with Size

Lecture 374 Directing Attention with Position (Part 1)

Lecture 375 Directing Attention with Position (Part 2)

Section 49: Week 11 - Day 49

Lecture 376 Cognitive Load

Lecture 377 Too Much Cognitive Load Examples

Lecture 378 Tip 1: Use Chunking

Lecture 379 Tip 2: Give Control

Lecture 380 Tip 3: Break Into a Story

Lecture 381 Tip 4: Use Colour Sparingly

Lecture 382 Tip 5: Avoid Redundant Encoding

Section 50: Week 11 - Day 50

Lecture 383 Tip 6: Integrate The Legends

Lecture 384 Tip 7: Maximise The Data-ink Ratio

Lecture 385 Tip 8: Master Tooltips & Annotations

Lecture 386 Cleveland and McGill's Ranking of Elementary Perceptual Tasks (Part 1)

Lecture 387 Cleveland and McGill's Ranking of Elementary Perceptual Tasks (Part 2)

Lecture 388 Tip 9: Simpler Charts Are (Often) Better

Lecture 389 Tip 10: Use Titles to Ask Questions

Section 51: Week 11 - Day 51

Lecture 390 Intro to The Truthful Charts

Lecture 391 Part 1 - Gestalt Principles

Lecture 392 Law of Similarity (Part 1)

Lecture 393 Law of Similarity (Part 2)

Lecture 394 Law of Similarity (Part 3)

Lecture 395 Law of Pragnanz (Part 1)

Lecture 396 Law of Pragnanz (Part 2)

Section 52: Week 11 - Day 52

Lecture 397 Law of Proximity (Part 1)

Lecture 398 Law of Proximity (Part 2)

Lecture 399 Law of Continuity (Part 1)

Lecture 400 Law of Continuity (Part 2)

Lecture 401 Law of Continuity (Part 3)

Lecture 402 Law of Closure

Section 53: Week 11 - Day 53

Lecture 403 Law of Common Region (Part 1)

Lecture 404 Law of Common Region (Part 2)

Lecture 405 Axis Expectations

Lecture 406 Size Expectations

Lecture 407 Color Expectations

Section 54: Week 12 - Day 54

Lecture 408 The Narrative Arc

Lecture 409 The Cinderella Story

Lecture 410 Story Analysis 1 - Sea Turtles in Curacao

Lecture 411 Story Analysis 2 - Tennis Hero Boris Becker

Lecture 412 Story Analysis 3 - Save the Big Cats

Lecture 413 Story Analysis 4 - US Car Accidents 2019

Lecture 414 Storytelling With Data

Take this course if you want to learn Tableau completely from scratch,Take this course if you want to Boost your Career by becoming Tableau Certified!,Take this course if you are an advanced user who wants to make sure there are ZERO Gaps in your Tableau knowledge,Take this course if you love Hands-On Challenges with Super-Exciting Datasets! (Uniquely curated for this course),Data Analysts who want to master advanced Tableau techniques and achieve the Tableau Certified Professional certification.,Business Intelligence Professionals seeking to elevate their data visualization skills to a professional level.

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