Dashboard Foundations

tags: DF SLD

Version 6.0 - April 2022
Rafael J. BARROS

• Dashboard Foundations
  • New to MS Teams?
  • The DATA Process
  • Week 1: Dashboard Foundations
    • Examples from Slides DF-02: Dashboard
    • Examples from Slides DF-03: Marking and Filter
  • Explore dashboards on your own
  • Ice-Break activity
  • Week 2: Deduce & Acquire
    • Deduce Analytical Questions
    • ABCDEF Process: Deduce Template
    • Acquire the best Data available
    • Basic Visualizations
  • Week 3: Tidy Data
    • Data structure changes [Form]
    • Data semantic changes [Meaning]
    • The rules
  • Example 1: Structural changes
    • Step 1: Split the column
    • Step 2: Create a new data table to enable unpivot

New to MS Teams?

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Check these guidelines to learn more about this tool.

The DATA Process

Week 1: Dashboard Foundations

Dashboard introduction. Experience using dashboards as an end user.

Week 1: Practicing Markings and Filters

Icebreaker: Share your card at Microsoft Teams

Examples from Slides DF-02: Dashboard

• https://www.tibco.com/covid19
• https://bit.ly/DS-TSXI-Operational
• https://bit.ly/DS-TSXI-Social
• https://bit.ly/DS-Rubric

Examples from Slides DF-03: Marking and Filter

• https://bit.ly/DS1-Markings
• https://community.tibco.com/wiki/spotfire-enablement-hub
• https://bit.ly/DS-Filters

Explore dashboards on your own

TIBCO Spotfire Overview:

• https://bit.ly/DF6W01 [Up to 100 points]

Ice-Break activity

Create your personal presentation card. The objective of this activity is to participate in the online ice-breaker activity and get familiar with the Microsoft Team Channels.

Your card must have the following data:

• Preferred Name
• Country of birth
• Country of residence
• Three sentences about you, one false and two truths.

Week 2: Deduce & Acquire

Deduce Analytical Questions

ABCDEF Process: Deduce Template

Acquire the best Data available

Basic Visualizations

Week 3: Tidy Data

Data cleaning is the process of wrangling and unifying messy and complex data sets for easy access and analysis.

Data structure changes [Form]

About the transformation of shape of the underlying data table.

Usual examples is to add or remove columns (width); add or remove rows (Height)

Data semantic changes [Meaning]

About changing the way we interpret the data. This is about the values in the cells.

The rules

1. Each type of observational unit forms a table.
2. Each variable forms a column.
3. Each observation forms a row.

Codd, E.F. "Further Normalization of the Data Base Relational Model."(Presented at Courant Computer Science Symposia Series 6, "Data Base Systems," New York City, May 24th–25th, 1971.) IBM Research Report RJ909 (August 31st, 1971). Republished in Randall J. Rustin (ed.), Data Base Systems: Courant Computer Science Symposia Series 6. Prentice-Hall, 1972.

Example 1: Structural changes

For this example we use the RD-SLD-DF-OS.xlsx Raw Data file.

Also available the DXP sample file exercise

Step 1: Split the column

At the Data in analysis flyover, select the column you want to split and press the Action: Split column…

Verify the recommended suggestion is what you want:

You may change any of the parameters, for example the separator.

Step 2: Create a new data table to enable unpivot

We can't do unpivot on calculated columns like Split([column],"|",1)