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Data Management and Visual Analytics with Microsoft Excel

Duration

Course Code

2 Days

IV-DA-005

About the Course

This two-day comprehensive course provides a solid foundation in data management and visual analytics using Excel. Designed for both beginners and intermediate users, the course aims to enhance participants’ skills in organizing, cleaning, and managing data efficiently while equipping them with the tools to create meaningful visualizations that support data-driven decision-making.


Day 1 focuses on data organization, cleaning, and core functions for efficient data handling, while Day 2 dives into creating insightful visualizations and interactive dashboards. By the end of the course, participants will be equipped to turn raw data into valuable insights through Excel’s powerful features.


Course Objectives


  1. Understand Data Management Principles.

    1. Learn the foundational principles of data management and how they can be applied within Excel to organize and structure data effectively.

    2. Gain insights into best practices for data entry, organization, and table structuring to ensure accuracy and readiness for analysis.

  2. Master Data Import and Cleaning Techniques.

    1. Import data from various sources, including CSV files, databases, and web sources.

    2. Clean and prepare data for analysis, using techniques such as removing duplicates, handling missing values, and using Power Query to shape and transform data.

  3. Apply Essential Excel Functions for Data Analysis.

    1. Become proficient in key data functions, including SUM, AVERAGE, and COUNT, along with advanced lookup, logical, and aggregation functions that support complex data handling.

  4. Ensure Data Accuracy and Security.

    1. Use data validation techniques to minimize entry errors and ensure consistency.

    2. Learn methods for protecting workbooks and worksheets to secure data integrity and privacy.

  5. Develop Data Visualization Skills.

    1. Understand the importance of data visualization in decision-making and learn how to select appropriate chart types for different data sets.

    2. Create, customize, and enhance charts for clearer and more impactful data presentations.

  6. Analyze Data with PivotTables and PivotCharts,

    1. Explore the power of PivotTables and PivotCharts for data analysis, including sorting, grouping, filtering, and interactive data filtering with slicers.

  7. Leverage Advanced Visualization Tools.

    1. Use conditional formatting and sparklines for quick insights and trend analysis, and gain familiarity with Power Query for advanced data shaping.

  8. Design Interactive Dashboards.

    1. Build effective dashboards by combining charts, tables, and slicers to create a cohesive and interactive experience for data exploration.


Day 1: Data Management in Excel


Module 1: Introduction to Data Management in Excel

  • Overview of Data Management Principles.

  • Excel as a Tool for Data Handling.

    • Organizing data in tables.

    • Data entry best practices.

    • Data structure and formatting for analysis.


Module 2: Data Importing and Cleaning

  • Importing Data from Various Sources.

    • CSV, Text, Databases, and Web data.

    • Connecting Excel to external data (Power Query).

  • Data Cleaning Techniques.

    • Removing duplicates, handling blank cells.

    • Transforming data using Power Query.

    • Text-to-columns, splitting and merging data.


Module 3: Excel Functions for Data Management

  • Essential Data Functions.

    • SUM, AVERAGE, COUNT, MIN, MAX.

  • Lookup and Reference Functions.

    • VLOOKUP/XLOOKUP, HLOOKUP, INDEX, MATCH.

• Logical Functions.

  • IF, AND, OR, IFERROR.

• Data Aggregation and Grouping.

  • SUMIFS, COUNTIFS, AVERAGEIFS.


Module 4: Data Validation and Protection

  • Setting Data Validation Rules.

    • Drop-down lists, input restrictions.

  • Protecting Workbooks and Worksheets.

    • Password protection and permissions.


Day 2: Visual Analytics in Excel


Module 5: Introduction to Data Visualization

  • Importance of Data Visualization in Decision Making.

  • Choosing the Right Chart Type for Your Data.

    • Bar, Line, Pie, Scatter, and Area Charts.

    • When to use each chart type.


Module 6: Creating and Customizing Charts

  • Basic Charts and Formatting.

    • Customizing chart elements: titles, labels, axes.

    • Adding trendlines and error bars.

  • Advanced Chart Types.

    • Combo charts.

    • Waterfall, Funnel, and Gantt Charts.


Module 7: PivotTables and PivotCharts for Data Analysis

  • Introduction to PivotTables.

  • Creating and formatting PivotTables.

    • Sorting, grouping, and filtering data.

  • PivotCharts for Visual Data Representation.

    • Slicers and Timelines for interactive filtering.


Module 8: Advanced Data Visualization Tools

  • Conditional Formatting for Data Insights.

    • Heat maps, Data bars, Color scales.

  • Sparklines for Trend Analysis.

  • Power Query for Data Shaping and Transformation.

    • Combining, merging, and transforming datasets.


Module 9: Building Dashboards in Excel

  • Principles of Dashboard Design.

    • Structuring a dashboard for clarity and impact.

  • Creating Interactive Dashboards.

    • Combining charts, PivotTables, and slicers.

    • Using hyperlinks and form controls for navigation.

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