Tableau Prep: Up & Running: Self-Service Data Preparation for Better Analysis

Tableau Prep: Up & Running: Self-Service Data Preparation for Better Analysis

Book Description
For self-service data preparation, Tableau Prep is relatively easy to use—as long as you know how to clean and organize your datasets. Carl Allchin from The Information Lab in London gets you up to speed on Tableau Prep through a series of practical lessons that include methods for preparing, cleaning, automating, organizing, and outputting your datasets.
Based on Allchin’s popular blog, Preppin’ Data, this practical guide takes you step-by-step through Tableau Prep’s fundamentals. Self-service data preparation reduces the time it takes to complete data projects and improves the quality of your analyses. Discover how Tableau Prep helps you access your data and turn it into valuable information.
  • Know what to look for when you prepare data
  • Learn which Tableau Prep functions to use when working with data fields
  • Analyze the shape and profile of your dataset
  • Output data for analysis and learn how Tableau Prep automates your workflow
  • Learn how to clean your dataset using Tableau Prep functions
  • Explore ways to use Tableau Prep techniques in real-world scenarios
  • Make your data available to others by managing and documenting the output


1. Why Self-Service Data Prep?

I. Getting Started
2. Getting Started with Tableau Prep Builder
3. Planning Your Prep
4. Shaping Data
5. Connecting to Data in Files
6. Connecting to a Database

II. Data Types
7. Dealing with Numbers
8. Dealing with Dates
9. Dealing with String Data
10. Dealing with Boolean Data

III. The Shape of Data
11. Profiling Data
12. Sampling Data Sets
13. Pivoting Columns to Rows
14. Pivoting Rows to Columns
15. Aggregating in Prep Builder
16. Joining Data Sets Together
17. Unioning
18. Calculations

IV. Output
19. Choosing an Output
20. Outputting to a Database
21. Getting Started with Tableau Prep Conductor
22. Creating Additional Data
23. Filtering
24. Removing Data During Input
25. Splitting Data Fields
26. Cleaning by Grouping Data
27. Dealing with Nulls
28. Using Data Roles
29. Dealing with Unwanted Characters
30. Deduplicating
31. Using Regular Expressions
32. Completing Advanced Joins
33. Creating Level of Detail Calculations
34. Doing Analytical Calculations

VI. Beyond the Basics
35. Breaking Down Complex Data Preparation Challenges
36. Handling Free Text
37. Using Smarter Filtering
38. Managing Conversion Rates
39. Scaffolding Your Data
40. Connecting to Programming Scripts
41. Handling Prep Builder Errors

VII. Managing Your Data
42. Documenting Your Data Preparation
43. Deciding Where to Prepare Your Data
44. Managing Data
45. Storing Your Data46. Using Identifiers and Keys in Data
47. Keeping Your Data Up-to-Date
48. Using History Tables
49. Evaluating Whether You Need Prep Builder at All
50. Final Thoughts

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