Explore fundamentals of data visualization

  2 minute read  

https://docs.microsoft.com/en-us/learn/modules/explore-fundamentals-data-visualization/

Data modeling and visualization is at the heart of business intelligence (BI) workloads that are supported by modern data analytics solutions. Essentially, data visualization powers reporting and decision making that helps organizations succeed.

Describe Power BI tools and workflow

https://docs.microsoft.com/en-us/learn/modules/explore-fundamentals-data-visualization/2-power-bi

  • Enterprise-scale business analytics
  • integrated solution
  • Supports complex data modeling
  • Interactive reporting
  • Secure sharing

Microsoft Power BI

Microsoft Power BI is a suite of tools and services that data analysts can use to build interactive data visualizations for business users to consume.

Power BI Desktop > Power BI Service > Web Browser / Power BI Phone App

Power BI Desktop

  • Windows application
  • Import data
  • Combine and organize the data
  • Create data models
  • Create reports

Power BI Service

  • Cloud service
  • Publisher of the Power BI Desktop report
  • Big data modeling and report editing (limited)
  • Schedule data refreshes
  • Share reports with others
  • Define dashboards and apps

Describe core concepts of data modeling

https://docs.microsoft.com/en-us/learn/modules/explore-fundamentals-data-visualization/3-data-modeling

  • Analytical models enable you to structure data to support analysis
  • Models are based on related tables and define
    • numeric values to analyze (measures)
    • entities by which they are aggregated (dimensions)
  • For example a model may contain
    • numeric data; sales
    • dimension data; products, customers, and time
  • You could aggregate sale measure across different dimensions
  • This is known as a CUBE

Tables and schema

  • A dimension table contains the entities that you want to aggregate; so multiple tables each containing specific data such as sales, customer, etc
  • Each entity has a row with a unique key then whatever values are needed for that table
  • A fact table is the aggregation of the values you require from the various dimension tables
  • This type of schema is called a star; you have the central fact table being fed data from the surrounding dimension tables
  • A more complex schema with additional layers of dimension tables is called a snowflake

Attribute hierarchies

By combining values, such as year month day, you can quickly drill up or down in the tables to for example so all sales for a particular year or for a certain day within that year.

Describe considerations for data visualization

https://docs.microsoft.com/en-us/learn/modules/explore-fundamentals-data-visualization/4-data-visualizations

Data can be visualy represented in various different ways such as

  • Tables and text
    • Simple
    • Numerous values must be displayed
  • Bar and column charts
    • Compare numeric values for discrete categories
  • Line charts
    • Compare categorized values
    • Examine trends over time
  • Pie charts
    • Compare values as proportions of a total
  • Scatter plots
    • Compare two numeric measure and identify a relationship between them
  • Maps
    • Compare values for different geographic areas
Last modified July 21, 2024: update (e2ae86c)