Difference between Power Query and Power Pivot

Question

What is the difference between Power Query and Power Pivot

Jaish Mathews · Answer

PowerPivot is related to working with data, but it is more than just pivoting data as you described. Difference from Traditional Pivot Traditional Pivot : Works on a single table and focuses on summarizing data through simple rearrangements. PowerPivot : Supports multiple tables, complex relationships, and advanced calculations. If you're familiar with databases, you can think of PowerPivot as a bridge between the simplicity of Excel and the power of a relational database. It enables both basic pivoting tasks and more complex data modeling.

Jay Krishna Reddy · Answer

Yes, you're absolutely right! The process of transforming data in a database table by switching the orientation of rows and columns is indeed related to database pivoting.

Jaish Mathews · Answer

Power Query and Power Pivot are two powerful tools in Microsoft Excel and Power BI that serve distinct purposes but often complement each other. Here's a comparison: Power Query Purpose: Data extraction, transformation, and loading (ETL). Functionality: Connects to various data sources (e.g., databases, files, web services). Cleans, transforms, and reshapes data (e.g., removing duplicates, filtering, pivoting/unpivoting). Automates repetitive data preparation tasks. Interface: A user-friendly query editor with step-by-step transformation logs. Output: Produces a clean, ready-to-use table or dataset loaded into Excel or Power BI. Use Case: Preparing raw data for analysis by cleaning and structuring it. Power Pivot Purpose: Advanced data modeling and analysis. Functionality: Builds relationships between different datasets (like a relational database). Creates calculated fields and measures using Data Analysis Expressions (DAX). Handles large datasets efficiently through an in-memory data model. Provides advanced aggregation and analytical capabilities. Interface: The Power Pivot window for managing data models and writing DAX formulas. Output: Produces insights and visualizations using relationships and measures. Use Case: Performing complex analysis and aggregations on prepared data. Key Differences Feature Power Query Power Pivot Purpose Data preparation (ETL) Data modeling and analysis Transformation Tools Extracts and transforms data Creates relationships and measures Language M (Power Query formula language) DAX (Data Analysis Expressions) Output Cleaned datasets Data models, calculated fields Memory Efficiency Not memory-intensive Optimized for large datasets How They Work Together Power Query is often used first to extract, clean, and shape data. The transformed data is loaded into the Power Pivot data model, where relationships are defined, and advanced calculations are performed. Together, they enable seamless end-to-end data processing, analysis, and visualization. Would you like detailed examples or scenarios for their use?

Kiran Kumar · Answer

Hi Jaish I accept your answer, but I know pivot in database Is it something related to database pivot that is changing columns into rows and vice versa rows into columns