Data Modeling with Microsoft Excel : Model and Analyze Data Using Power Pivot, DAX, and Cube Functions

Data Modeling with Microsoft Excel Model and Analyze Data Using Power Pivot, DAX, and Cube Functions

Microsoft Excel's BI solutions have evolved, offering users more flexibility and control over analyzing data directly in Excel. Features like PivotTables, Data Model, Power Query, and Power Pivot empower Excel users to efficiently get, transform, model, aggregate, and visualize data. Data Model...

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Detalles Bibliográficos
Otros Autores: Boateng, Bernard Obeng, author (author), Olafusi, Michael, author
Formato: Libro electrónico
Idioma:Inglés
Publicado: Birmingham, England : Packt Publishing Ltd [2023]
Edición:First edition
Materias:
Microsoft Excel (Computer file)
Data structures (Computer science)
Electronic spreadsheets > Computer programs.
Ver en Biblioteca Universitat Ramon Llull:https://discovery.url.edu/permalink/34CSUC_URL/1im36ta/alma991009785404506719
Tabla de Contenidos:
  • Cover
  • Title Page
  • Copyright and Credits
  • Foreword
  • Contributors
  • Table of Contents
  • Preface
  • Part 1: Overview and Introduction to Data Modeling in Microsoft Excel
  • Chapter 1: Getting Started with Data Modeling - Overview and Importance
  • Understanding the concept of data modeling
  • Comparing a one-table analysis to multiple-table analysis in Microsoft Excel
  • Practical use cases for a data model
  • The accountant
  • The salesperson
  • Introduction to Power Pivot, Excel versions, and installation
  • How do I install Power Pivot?
  • Exploring the features of Power Pivot
  • What is DAX?
  • Best practices with Power Pivot
  • Summary
  • Questions for discussion
  • Chapter 2: Data Structuring for Data Models
  • Data structuring - understanding the three golden rules
  • Understanding data redundancy
  • Problems caused by data redundancy
  • What is data normalization?
  • Denormalized and normalized data
  • Understanding table relationships
  • One-to-many relationship
  • Many-to-many relationship
  • One-to-one relationship
  • Understanding dimension and fact tables
  • Fact table - sales
  • Dimension table - product
  • Dimension table - customer
  • Dimension table - date
  • Understanding the role of primary keys and foreign keys
  • Summary
  • Key terms in this chapter
  • Questions for discussion
  • Chapter 3: Preparing Your Data for the Data Model - Cleaning and Transforming Your Data Using Power Query
  • Understanding connections and queries
  • Connections
  • Queries
  • An overview of the Power Query editor
  • Getting your data type right
  • Add Column or Transform?
  • Merging and appending data using Power Query
  • Summary
  • Chapter 4: Data Modeling with Power Pivot - Understanding How to Combine and Analyze Multiple Tables Using the Data Model
  • Adding queries/tables to your data model
  • Adding columns to your data model.
  • Creating calendar tables
  • Creating relationships using primary and foreign keys
  • Understanding the different types of schemas (snowflake and star)
  • Creating hierarchies
  • Hiding fields and tables from client tools
  • Summary
  • Section 2: Creating Insightful Calculations from your Data Model using DAX and Cube Functions
  • Chapter 5: Creating DAX Calculations from Your Data Model - Introduction to Measures and Calculated Columns
  • DAX as a calculated column or measure
  • Creating your first measure - where to go
  • Common DAX functions (time intelligence, FILTER, CALCULATE, and so on)
  • Understanding row and filter contexts
  • Editing your DAX formulas
  • Summary
  • Chapter 6: Creating Cube Functions from Your Data Model - a Flexible Alternative to Calculations in Your Data Model
  • What are cube functions?
  • When do we use cube formulas?
  • Exploring cube functions in Microsoft Excel
  • CUBEVALUE
  • Adding slicers to your cube formulas
  • CUBEMEMBER
  • CUBESET
  • CUBESETCOUNT
  • CUBERANKEDMEMBER
  • Spilling cube functions with dynamic array formulas
  • Summary
  • Section 3: Putting it all together with a Dashboard
  • Chapter 7: Communicating Insights from Your Data Model Using Dashboards - Overview and Uses
  • What are dashboards?
  • Factors to consider when laying out your dashboard
  • Purpose and audience
  • Clarity and simplicity
  • Hierarchy and organization
  • Consistency and visual harmony
  • Interactivity and user controls
  • Data visualization techniques
  • Accessibility and documentation
  • Common dashboard elements
  • PivotTables
  • Charts
  • Text boxes and labels
  • Images and shapes
  • Sparklines
  • Conditional formatting
  • Making your dashboard interactive
  • Slicers
  • Hyperlinks
  • Summary
  • Chapter 8: Visualization Elements for Your Dashboard - Slicers, PivotCharts, Conditional Formatting, and Shapes.
  • Laying out your dashboard using mockups or wireframes
  • Enter mockups and wireframes
  • Practice your mockup in Excel
  • Using shapes as cards in your dashboards
  • Inserting conditional formatting and sparklines
  • Sparklines
  • Conditional formatting
  • Adding and formatting charts
  • Inserting slicers for interaction
  • Summary
  • Chapter 9: Choosing the Right Design Themes: Less Is More with Colors
  • Understanding your users
  • Know your audience's preferences
  • Accessibility is key
  • Consistency is crucial
  • How to reduce noise in your presentation
  • Using colors to tell a story
  • Associative colors
  • Using gradient colors for scales
  • Highlighting key data
  • Summary
  • Chapter 10: Publication and Deployment: Sharing with Report Users
  • Protecting your workbook
  • Skill one - restricting access to sensitive parts of your workbook
  • Collaboration
  • Skill two - inviting people to collaborate
  • Publishing a view-only online version via OneDrive/SharePoint
  • Skill three - using OneDrive/SharePoint as a means to share your final work
  • Exporting your data model to Power BI
  • Summary
  • Index
  • Other Books You May Enjoy.

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