Foreläsning 10 Diagram Kardinalitet och Power BI (3)

Page 1: Introduction to Power BI

• Mittuniversitetet (Mid Sweden University) is featuring Power BI in their presentations.

Page 2: Graphs in Power BI

• Focus on the use of graphs and data visualization in Power BI.

Page 3: Line Chart Analysis

• Displays a line chart with yearly data from 1800 to 2000.

• Key metrics depicted, likely relating to population or economic data with marked declines in the past.

• Uses numerical markers for values from 0 to 110,000.

Page 4: Streaming Statistics

• Y-axis: Weekly streams (in millions) of Mariah Carey's "All I Want for Christmas is You".

• Significant peak during Christmas week with over 41 million streams.

• Chart spans from November 11 to December 30, 2021, with precise weekly breakdowns:

  • 02/12/2021: 24.18 million streams

Page 5: Revenue per Department

• Bar chart showcasing revenue data for various departments at ICA Maxi.

• Y-axis: Revenue in SEK from 0 to 700,000.

• Departments charted include:

  • Special

  • Bakery (Bageri)

  • Dairy (Mejeri)

  • Dry Goods (Torrvaron)

  • Deli (Charkuteri)

  • Fruits & Vegetables (Frukt & Grönt)

Page 6: Football Players' Preferred Foot

• Pie chart illustrating the preference of football players' dominant foot.

• Data breakdown:

  • Right-footed: 75.0%

  • Both-footed: 10.0%

  • Left-footed: 15.0%

Page 7: Creative Visualization

• Analogy: A pizza serves as a real-time pie chart indicating remaining slices.

  • Emphasizes the concept of visualization in data representation.

Page 8: Correlation Diagram

• Displays a correlation chart indicating anomalies and clusters among data points.

• Values range on the Y-Axis from 0 to 80, possibly linking to health conditions or statistical data analysis.

Page 9: Bubble Chart Overview

• Placeholder for a bubble chart, suggesting graphical representation of data points categorized by size.

Page 10: BBC Four Income Analysis

• Financial chart detailing income statistics.

• Indicates values ranging from $400, $4,000 to $40,000, possibly across different years or segments.

Page 11: Performance Overview

• Evidence of statistical reflections on Daniel Stensson’s performance across various skills.

• Metrics may include:

  • Average Completion

  • Dribbling

  • Aerial Duels

  • Passing Play

  • Defensive Play

Page 12: Cardinality Concept

• Exploring cardinality in database structure and its significance in data relationships.

• Potential reference to concepts like primary keys.

Page 13: One-to-One Cardinality

• Illustrating a one-to-one relationship between entities within data frameworks.

Page 14: Unique Relationships

• Further emphasis on one-to-one cardinality with contextual examples of marital relationships.

Page 15: One-to-Many Cardinality

• Discusses how one entity can be related to multiple entities and the implications for data relationships.

Page 16: Fact Tables & Lookup Tables

• Overview of the distinction between fact tables and lookup tables in databases.

Page 17: Customer Transactions Example

• Example of a fact table displaying customer transaction data:

  • Customer details include: Customer Number, Name, Home Town.

  • Purchase records detail products bought alongside pricing and quantities.

Page 18: Team Data Overview

• Listing of various teams, their cities, and estimated population statistics, likely focused on football clubs across Europe.

  • Clubs mentioned include:

    • AC Milan

    • FC Barcelona

    • Bayern Munich

    • Real Madrid

• Categorizing cities based on size (e.g., large, medium, small).

Page 19: Semantic Modeling

• Introduction to semantic modeling concepts as they pertain to data analytics and BI solutions.

Page 20: Market Share Analysis

• Market share data depicted across different metrics and categories, potentially visualizing growth or decline.

• Includes both on-premise and cloud-based data management comparisons.

Page 21: Workflow Steps

• Workflow for creating reports and dashboards using Power BI:

  1. Data Preparation

  2. Build Semantic Model

  3. Create Reports

  4. Create Dashboards

Page 22: Expanded Workflow

• Workflow detailing access methods:

  • Power BI Desktop

  • Power BI Service

  • Python (General and in Course)

Page 23: Power BI Tools Comparison

• Visual comparison between Power BI Service and Power BI Desktop, showcasing the respective functionalities and uses.

Page 24: Conclusion/Demonstration

• Final remarks on the use of Power BI at Mid Sweden University with a potential demonstration of features or case studies.