Overview
In today’s ever-growing world of data, analytics, business intelligence, and the ability to utilize data for driving business decisions, tools such as Tableau are increasingly valuable. Having quick access to data, being able to report on data, and filter, analyze, and model that data differentiates both
the efficiency and effectiveness in which we can perform our roles in today’s workplace.
Audience
This course is designed for students who are new or novice users of Tableau. It is assumed that the
student has a working knowledge and experience with data, datasets, analytics, dashboards and
reporting in general. These may be via tools other than Tableau.
Prerequisites:
It is highly recommended that the students have Tableau* on their computer as this class is technical and hands-on based.
*If the student does not yet have Tableau software, we can provide directions for a free 14-day trial. It is up to the student/client to confirm downloading this to either their work computer or personal computer prior to class as most agencies need their IT Help Desk to execute a download.
Length
1 day
Outline
Part I
Introduction to BI and Data Visualization
- Overview of BI
- Importance of good data visualizations
- Selection of visualization types
Components of BI “stack”
- Business analytics, data mining, visualization tools
- Operational systems, data warehouse
- Data governance, reporting tools
Tableau vs. Excel
- Comparison in ease of use, visualizations, scalability
Data Types and Profiling
- Understanding different data types
- Handling missing data, data distributions
Building Good Visualizations
- Flow chart – picking a visualization type
- Resources for further reading
Data Modeling in BI
- Data modeling definition and overview
- Denormalized data, star schema
- Normalization in data modeling
- Resources for further reading
Overview of Tableau Features
- Data visualization, analysis
- Dashboard creation, reporting
Tableau Interface Elements
- Tableau workspace UI elements
- Data Sources UI elements
Data Sources in Tableau
- Overview of data sources and their differences
- Databases
- Text files
- MS Access
- Excel
Live vs Extract Data
- Describe Live vs Extract data source type
- Rule of thumb for picking Live or Extract
Blue and Green Pills – Measures and Dimensions
- Measures vs Dimensions
- Discrete vs continuous
Part II
Hands-on Demo/Exercise – Northwind example data
- Importing MS Access data
- Creating Groups
- Joining multiple tables
- Creating sheets, visualizations, dashboards
- Working with basic filters
- Visual actions and interactivity
Dashboard and Stories Creation
- Review features and options for dashboard creation and styling
- Best practices for Dashboards
- Review process and configuration for building a Story
Data Terminology
- Review key terminology now that we’ve seen Tableau in action
Part III
Practice Exercise & Demo – Sample Superstore dataset
- Extract vs Live demo and configuration
- Dataset filters and behavior with Extract or Live
- Saving an extract file
- “Show Me” panel for plot type selection
- “Marks” tile for visual configuration
Student Exercise – Sample Superstore
- Open Sample Superstore as “Live”
- Apply a date range filter
- Create bar plot sum of sales by Quarter+Month
Working with Cols and metadata
- Splitting columns
- Rename columns
- Aliases
- Calculated columns
- Bins and histograms
- Editing axis configuration
Example Plot Types
- Show Highlight table, Scatter plot, treemap, histogram
Sharing a Data Source Connection
- Publishing from Desktop
- Sharing from Cloud or Server
Data Operations: Joins
- Join types – left, right, inner, outer
- Join examples
- Creating joins in Tableau Desktop
Part IV
Student Exercise – build relationships from excel source
- Open “More Excel Data.xls”
- Follow instructions for creating relationships among 4 tables
- Produce a plot of Sames Amount by Year, Product Category and Product Sub-category
Data Operations: Blending
- Definition of Blending
- How to work with Blends in Tableau Desktop
- Guidelines for using Blend, Join or Relationships
Going Deeper with Filters
- Additional options for using filters on report elements or datasets
Summary and Q&A
- Review main points covered
- Open time for Q&A or additional hands-on demo work