CHAPTER 1:

CREATING VISUAL ANALYTICS WITH TABLEAU DESKTOP

THE BUSINESS CASE FOR VISUAL ANALYSIS

Regardless of whether they are profit-oriented or not, every entity seeks insights from the data they generate. This is the primary focus of most analysis tools. The required insights are crucial for guiding entities in maintaining efficiency, pursuing opportunities, and proactively preventing negative outcomes. To effectively support entities in fulfilling these functions, data generation and analysis can be categorized into three types:

• Known Data (Type 1)
• Data You Know You Need to Know (Type 2)
• Data You Did Not Know You Need to Know (Type 3)

Known Data (Type 1):

This type of report depicts basic daily operations. Its intention is not to answer operational questions but rather to inform users about how the day ended. The content is often basic, representing already known information in a report format.

Data You Know You Need to Know (Type 2):

Patterns often emerge from the known data report above. These patterns typically prompt questions such as "Why is this happening?" A good example is outliers, which managers of operations will be interested in understanding the cause of. The cause of these outliers can be derived by examining the report data and identifying anomalies within the data set. Essentially, the purpose of a Type 2 report is to provide answers to questions for which we already know the answers.

Data You Did Not Know You Need to Know (Type 3)

Within the type 1 and type 2 lies the types of insight which are not readily visible except with the help of analytic tools such as Tableau. Tableau provides the possibility of seeing patterns and outliers that are not readily detectable with ordinary report, thus, this will creates opportunity of providing a solutions to a questions that might not have ordinary being thought of. The process of breaking down the data into smaller parts provide the channels of gaining an useful insight that can is often useful in the prediction of future patterns.

TURNING DATA INT0 INFORMATION WITH VISUAL ANALYTICS

Often than not that data losses it richness when it is overly summarised. The decision makers comprised decision if the available data is inadequate. With the help of the visual analytics tools, the challenge of overly summarizing data is solved by the use of the tooltips that pops out when you point your mouse on a particular detail. The ideal analysis and reporting tool should possess the following attributes:

1. Simplicity: Easy for non-technical users
2. Connectivity: Ability to connect to large variety of datasources
3. Visual competence: Good visualisation of information
4. Sharing: Facilitate sharing of insight
5. Scale: Handle large data set.

THE TABLEAU MENU

1. File menu
2. Data Menu
3. Worksheet menu
4. Dashboard menu
5. Analysis menu
6. Map menu
7. Format menu
8. Server menu
9. window menu
10. Help menu

Tableau Toolbar Button Reference

• In Tableau Desktop, you can hide or display the Tableau toolbar by selecting Window > Show Toolbar.

DATA TYPES

All fields in a data source have a data type. The data type reflects the kind of information stored in that field, for example integers (410), dates (1/23/2025) and strings ("Belgium"). The data type of a field is identified in the Data pane by one of the icons shown below.