Excel beyond 1 million rows: A reality very few of us know about

I always hear Excel can′t handle >1MM rows and that's a major limitation of the tool. And that makes many of us turn to Python to do it.

What if I told you that newer versions of Excel, specifically Excel 2010 and onwards, are fully capable of handling large datasets with way more 1 million rows?

Enter Excel′s Power Query and Power Pivot!

Power Query allows us to extract, transform, and load data from various sources, ensuring the data is clean and ready for analysis.

On the other hand, Power Pivot let us create sophisticated data models, establish relationships between tables, and perform custom calculations.

These tools have transformed Excel into a powerful data analysis tool, capable of handling big data beyond the 1,048,576 row limitation.

So far, I′ve been able to reach 6 MM rows in a simple test, with a pivot chart to sum up information.

A quick summary of each of the power tools:

Power Pivot:

• Power Pivot is a data modeling tool that allows users to analyze large datasets with ease.
• It enables users to establish relationships between different tables, create calculated columns and measures, and create sophisticated data hierarchies.
• Power Pivot is great for managing complex data models, creating custom calculations, and creating data visualizations.
• It uses the DAX formula language, allowing users to make use of variables and powerful context manipulation.
• Power Pivot enables us to work with big data beyond the 1,048,576 limitation and still produce smaller, leaner and faster workbooks than a standard PivotTable.

Power Query:

• Power Query is an ETL (Extract, Transform, Load) self-service tool that works like an Excel add-in.
• It allows users to extract data from various sources, manipulate the specified data into a form that matches their needs, and load it into Excel.
• Power Query can connect to a vast number of data connectors, ranging from data sources such as TXT, CSV, and Excel files, to databases such as Microsoft SQL Server, and popular SaaS services.
• It provides capabilities for data cleansing and transformation activities, such as filtering, adding columns, changing shape, text, number, date operations etc.
• Power Query can automate data collection, clean-up, and publishing processes.
• It’s always recommended to filter your data in the early stages of your query or as early as possible.

Power Query and Power Pivot working together:

• Power Query and Power Pivot complement each other.
• Power Query is the recommended experience for importing data.
• Power Pivot is great for modeling the data you’ve imported.
• Use both to shape your data in Excel so you can explore and visualize it in PivotTables, PivotCharts, and Power BI.

These tools are particularly useful when dealing with big data. They allow for efficient analysis and quicker insights, transforming the way businesses handle data.

With the help of Power Query and Power Pivot, we can take full advantage of Excel’s data modeling capabilities to gain deeper insights into their data and make informed decisions.