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Course Outline

Introduction

Overview of Tableau Prep Builder

  • Definition and purpose of Tableau Prep Builder
  • Primary capabilities and advantages for data preparation workflows
  • System interface and navigation guidelines

Role of Prep Builder Within the Tableau Architecture

  • Synergy with Tableau Desktop and Tableau Server environments
  • Function within the broader data analysis and visualization lifecycle

Data Connection Methodologies

  • Establishing links to cloud-based repositories (e.g., Google Sheets, AWS)
  • Connecting to local file formats (Excel, CSV, database systems)
  • Evaluating data formats and storage architectures

Administration of Data Connections

  • Configuring data storage parameters
  • Distinguishing between live connections and extracted data snapshots

Data Cleansing and Structuring

  • Detection and remediation of null values and incomplete records
  • Operations for splitting, renaming, and merging fields
  • Application of filters and grouping mechanisms to facilitate analysis

Fundamental Data Transformations

  • Execution of pivoting, unpivoting, and aggregation processes
  • Conducting joins and unions across distinct datasets
  • Leverage the Data Interpreter feature for automated data cleanup

Integration of Multiple Data Sources

  • Joining data from heterogeneous formats (cloud, local, database)
  • Effective strategies for blending and merging datasets
  • Implementation of full, inner, left, and right join types

Complex Integration Techniques

  • Utilization of relationships to link disparate datasets
  • Differentiation between join and blend methodologies

Development of Calculated Fields

  • Fundamental calculations including arithmetic, string manipulation, and date functions
  • Logical functions (IF, CASE) for structured data manipulation

Data Processing Operations

  • Data aggregation techniques (sum, average, minimum, maximum)
  • Development of dynamic calculated fields and their application to datasets
  • Custom calculations tailored to specific operational requirements

Publishing to Tableau Server and Tableau Online

  • Procedures for publishing prepared data for analytical review
  • Scheduling automated updates for published datasets

Administration of Data Updates

  • Refreshing data sources within the Tableau Prep Builder environment
  • Automating workflow updates and executing associated scripts

Comprehension of Geographic Data

  • Assignment of geographic roles in Tableau (Country, City, Postal Codes, etc.)
  • Data preparation for mapping applications (latitude/longitude coordinates, geocoding)

Construction of Basic Maps

  • Generation of fundamental maps utilizing geographic data
  • Customization of map visual attributes (color, scale, detail level)

Utilization of Map Layers

  • Incorporation of additional data layers into maps to enhance analytical depth
  • Development of map interactions and filter mechanisms

Management of Custom Geographies

  • Importation of custom shape files (e.g., regional or demographic boundaries)
  • Plotting data against non-standard geographic divisions

Development of Filled Maps and Density Visualizations

  • Visualization of data density across specified regions
  • Generation of filled geographic maps based on targeted fields

Advanced Mapping Capabilities

  • Construction of dual-axis maps to support complex insights
  • Application of map layers and filters to produce interactive geographic visualizations

Practical Application: Data Preparation and Mapping

  • Integration of data from cloud sources and execution of transformations
  • Development of calculated fields and operational logic in Prep Builder
  • Construction of a comprehensive map dashboard using prepared data

Case Studies and Operational Applications

  • Resolution of business challenges through Tableau Prep and mapping tools
  • Development of end-to-end data pipelines from connection to visualization

Summary and Next Steps

Requirements

  • Fundamental understanding of data principles, such as file structures (e.g., CSV, Excel) and storage mechanisms
  • Proficiency in computer operation and navigation of software applications

Audience

  • Data analysts seeking resources designed for government professionals
 21 Hours

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