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Easy Notes of Data Analytics unit- 3 @Computer Diploma

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Unit-III Data Analytics with Excel

3.1 Excel Dashboard: Tables and Data Grids, Dynamic Filters and Controls, Trend Analysis and Forecasting

3.2 Pivot Tables: Creating a Pivot Table Specifying Pivot Table Data

3.3 Changing a Pivot Tables, Calculation Filtering and Sorting a Pivot Table

3.4 Creating a Pivot Chart, Grouping Items

3.5 Updating a Pivot Table, formatting a Pivot Table using Slicers

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Description

3.1 Excel Dashboards & Trends

Dashboards turn raw data into a visual story for quick decision-making.

  • Tables & Data Grids: Structured referencing, auto-expansion, and banded rows for readability.

  • Dynamic Filters: Using Slicers and Timelines to filter multiple visuals simultaneously.

  • Form Controls: Checkboxes, scroll bars, and radio buttons to make reports interactive.

  • Trend Analysis: Identifying patterns over time (Linear, Exponential, or Moving Average).

  • Forecasting: Using the Forecast Sheet tool to predict future values based on historical data.

3.2 Pivot Tables: Fundamentals

The core tool for summarizing large datasets without complex formulas.

  • Source Data: The raw range or table used to build the Pivot.

  • Field List: The four quadrants: Filters, Columns, Rows, and Values.

  • Data Aggregation: Summarizing by Sum, Count, Average, Max, or Min.

  • Values Area: Where numerical data is calculated.

3.3 Calculations & Manipulation

Going beyond simple sums to extract deeper insights.

  • Calculated Fields: Creating new data columns (e.g., Profit = Revenue - Cost) inside the Pivot Table.

  • Show Values As: Displaying data as % of Grand Total, % of Column, or Running Total.

  • Sorting: Arranging data alphabetically or by value (largest to smallest).

  • Label/Value Filters: Filtering specific text or numerical thresholds (e.g., “Sales > 5000”).

3.4 Pivot Charts & Grouping

Visualizing summarized data and organizing categories.

  • Pivot Chart: A dynamic chart linked directly to a Pivot Table that updates as filters change.

  • Grouping Items: * Date Grouping: Collapsing daily data into Months, Quarters, or Years.

    • Numeric Grouping: Creating “bins” (e.g., grouping ages into 10-year brackets).

  • Drill Down: Double-clicking a value to see the underlying source records.

3.5 Updating & Formatting

Maintaining the accuracy and professional look of your analysis.

  • Refresh: Updating the Pivot Table when the underlying source data changes.

  • Change Data Source: Adjusting the range if new rows or columns are added.

  • Slicers: Visual buttons that act as “one-touch” filters.

  • Conditional Formatting: Applying Data Bars or Color Scales directly to Pivot Table cells.

  • Design Tab: Using Pivot Table Styles, Banded Rows, and Report Layouts (Tabular vs. Compact).

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