54 Days Of Tableau Complete Masterclass
Category: Tutorials
- views: 22
- date: 4 October 2024
- posted by: AD-TEAM
54 Days Of Tableau Complete Masterclass
Published 8/2024
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz
Language: English | Size: 27.89 GB | Duration: 49h 7m
Learn all Tableau aspects from Basic to Advanced and understand best visualisation principles
What you'll learn
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.
Requirements
You should have access to Tableau software.
Description
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 :)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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What you'll learn
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.
Requirements
You should have access to Tableau software.
Description
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 :)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
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