Data Models & Dashboards

Data Models & Dashboards

1-Day Course: Data Management & Power Pivot in Excel for Analytics & Dashboards

Target Audience: This course is designed for business users, and anyone who wants to leverage Excel and Power Pivot to transform data into valuable insights and visualisations.

Prerequisites: Basic to intermediate knowledge of Excel, including formulas, functions, and tables.

Course Objectives:

  • Gain confidence in data management principles within Excel.
  • Master Power Pivot for data cleaning, transformation, and modeling.
  • Build comprehensive and interactive Pivot Tables for advanced data analysis. Craft captivating and informative dashboards to tell data stories.

Morning Session:

Module 1: Data Management Essentials in Excel (2 hours)

  • Data organisation and cleaning techniques:
    • Importing and structuring data from various sources.
    • Identifying and correcting data inconsistencies.
    • Applying formatting and validation rules for data accuracy.
  • Formulas and functions for data manipulation:
    • Conditional formatting for visual insights.
    • Lookup and reference functions for data extraction.
    • Aggregation functions for summarising data.
  • Creating and managing Excel tables:
    • Leveraging table features for efficient data manipulation.
    • Utilising calculated columns and measures for extended analysis.
    • Building relationships between multiple tables.

Module 2: Power Pivot - Unleashing Data Analysis Power (2 hours)

  • Introduction to Power Pivot and its capabilities:
    • Understanding the in-memory data model and its advantages.
    • Exploring the Power Pivot interface and functionalities.
  • Data cleansing and transformation in Power Pivot:
    • Filtering and removing unwanted data points.
    • Splitting columns and creating new ones.
    • Creating calculated columns and measures for advanced analysis.
  • Building relationships between tables in Power Pivot:
    • Understanding different relationship types and their impact.
    • Creating and managing relationships for accurate data aggregation.

Afternoon Session:

Module 3: Mastering Pivot Tables with Power Pivot (2 hours)

  • Creating interactive Pivot Tables from Power Pivot data:
    • Choosing appropriate fields and measures for analysis.
    • Defining rows, columns, and filters for specific insights.
    • Formatting Pivot Tables for clear and concise data presentation.
  • Advanced Pivot Table techniques:
    • Calculated fields and measures for deeper analysis.
    • Slicers and timeline filters for interactive exploration.
    • Set analysis and calculated members for detailed breakdowns.

Module 4: Crafting Informative Dashboards in Excel (2 hours)

  • Understanding dashboard design principles:
    • Defining audience and objectives for clear communication.
    • Choosing appropriate charts and graphs for data visualisation.
    • Ensuring effective layout and visual hierarchy.
  • Building dashboards with Pivot Charts and Power Pivot data:
    • Combining multiple charts and graphs for comprehensive representation.
    • Formatting dashboards for visual appeal and clarity.
    • Adding interactive elements for user engagement.

Course Wrap-up (1 hour)

  • Recap and Q&A: Reviewing key learnings and addressing any questions.
  • Next steps and resources: Providing guidance for further exploration and practice.

Note: This 1-2-1 course outline is flexible and can be adjusted based on specific audience needs and time constraints. Hands-on practice exercises will be incorporated throughout the training to ensure understanding and retention.


Save £'s by booking onto one of our monthly courses listed below.

Data Models & Dashboards - Training Event

Event location: Venue TBC at one of our centres
Event start: 04/06/2024 09:30:00


Data Models & Dashboards - Training Event

Event location: Venue TBC at one of our centres
Event start: 02/07/2024 09:30:00


Data Models & Dashboards - Training Event

Event location: Venue TBC at one of our centres
Event start: 06/08/2024 09:30:00



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