Parquet is a highly efficient, columnar storage format used across analytics platforms like Hadoop, Spark, AWS Athena, and Azure Data Lake. While it’s excellent for storing and processing large datasets, many users still need to convert Parquet files into Excel (.xlsx) for reporting, sharing, or manual analysis.

This guide gives you a quick overview of the easiest ways to convert a Parquet file to Excel. 

What is a Parquet File?

Parquet is a columnar storage format widely used in big data systems like Apache Spark, Hadoop, AWS Athena, Azure Data Lake, and more.
It offers:

• Highly efficient data compression
• Faster read performance for analytical queries
• Schema evolution support
• Optimized storage for large datasets

However, Excel cannot directly open .parquet files, which is why users need a conversion process.

Why Convert Parquet to Excel?

You may want to convert Parquet to Excel when:

• The dataset needs to be shared with someone who doesn’t use big data tools
• You need to create reporting dashboards
• The data has to be viewed or manipulated in a spreadsheet
• A business team requires the data in a familiar format

Excel provides a simple and accessible format that works well for smaller datasets.

Convert Parquet to Excel Using Professional Solution

Users can efficiently convert their Parquet data files with the help of a professional solution like SysTools Parquet File Converter Software. A solution designed to smartly convert the desired .parquet files and effectively get the precise and accurate results. Here are the steps on how this conversion can be made. 

1. Install and open the suggested software.
2. Click Add File(s) and select your .parquet file
3. Choose Excel (XLSX) as the output format
4. Select destination path
5. Click Convert

That’s it — your Parquet file becomes a readable Excel workbook.

Using Python (Pandas + PyArrow)

A great option for developers or automation workflows.

import pandas as pd
df = pd.read_parquet("input.parquet")
df.to_excel("output.xlsx", index=False)

Using Apache Spark

Useful for extremely large Parquet files stored in data lakes.

from pyspark.sql import SparkSession
spark = SparkSession.builder.getOrCreate()
df = spark.read.parquet("input.parquet")
df.toPandas().to_excel("output.xlsx", index=False)

Final Thoughts

Converting Parquet files into Excel doesn’t have to be complicated. While coding tools like Pandas or Spark work well for developers, a professional tool offers the most user-friendly and reliable way to get clean, accurate Excel files without technical steps.