7 Best Data Wrangling Tools in 2026

You already know the struggle — hours spent wrestling with messy, disorganized data instead of extracting the insights you need. It’s frustrating, time consuming, and it pulls you away from the work that really matters. You didn’t sign up to spend your days cleaning up data; you need a solution that can handle the heavy lifting for you.

This is where data wrangling tools come into the picture. These tools are designed to ease and streamline the data preparation process so you can focus on what you do best: analyzing data, making informed decisions, and driving your business forward.

In this guide, we’ll explore the top data wrangling tools of the year, each offering unique features to address different needs. Read on to see how these tools can turn your data challenges into strategic advantages.

What Is Data Wrangling?

Data wrangling or Data Munging is the process of cleaning and preparing raw data for analysis. This preparation for automated data analytics encompasses several key activities:

• Data Extraction: Gathering data from various sources, including databases, spreadsheets, and APIs.
• Data Transformation: Converting data into a format suitable for analysis, which may involve aggregation, normalization, or reshaping.
• Data Cleaning: Identifying and correcting inaccuracies, inconsistencies, and missing values to improve data quality.
• Data Integration: Combining data from multiple sources to create a unified dataset.
• Data Enrichment: Augmenting existing data with additional information to provide more context or detail.
• Data Validation: Verifying the accuracy and completeness of data to make sure it meets required quality standards.

When selecting a data wrangling tool, it’s important to consider factors such as ease of use, integration capabilities, the complexity of your data sources, and cost effectiveness.

Why Do Businesses Need Data Wrangling Tools?

Data wrangling tools help overcome the challenges associated with managing data of varying quality from numerous sources. Let’s take a loot at the main reasons why businesses should be using data wrangling tools.

Handling Complex Data Sources

Businesses often get data from different systems like CRMs, ERPs, and social media. Each source has its own format, making it difficult to combine them manually. Data wrangling tools integrate and standardize this data, giving you a clear, unified view.

Ensuring Data Quality

Raw data can be messy, with errors, missing values, and duplicates. These issues can ruin analyses and misguide decisions. Data wrangling tools clean and correct data automatically to prepare it for effective analysis and maintain data accuracy and completeness.

Boosting Efficiency

Manually preparing data takes a lot of time and effort. Data wrangling tools automate repetitive tasks, saving time and reducing errors. They also scale with your data needs, handling larger datasets as your business grows.

An Overview

Before we explore the detailed functionalities of each data wrangling tool in our list, let’s have an overview of the top 7 tools that stand out in 2025.

These tools have been carefully selected based on their ease of use, scalability, and key features that cater to a wide range of data management needs.

Top 7 Data Wrangling Tools for 2025

1. Savant 

Savant offers a powerful platform for data preparation, transformation, and analysis, tailored to meet the needs of analysts and data teams.

With a focus on simplifying complex data workflows, Savant leverages no-code and low-code interfaces, allowing users to create and automate analytics processes without requiring extensive technical expertise.

The intuitive workflows combine dataflows and analytics, along with unique analytics bots. You can use Savant’s pre-built automation apps, create your own solutions, and enhance automation with AI, making data wrangling faster and more effective.

Key Features:

• Simplifies data workflows via drag-and-drop interface, making it accessible to users with varying levels of technical expertise.
• Incorporates AI-driven workflows to automate analytics tasks, providing insights faster with less manual effort.
• Handles large datasets and complex data sources, making it suitable for both small teams and large enterprises.
• Seamless integration capabilities with a wide range of data sources, including modern SaaS applications, to easily blend and analyze data from multiple origins.

Strengths:

• No-code/low-code approach makes it accessible to users without deep technical skills.
• The inclusion of AI-driven features allows for more efficient data processing and analytics, reducing the time required to gain actionable insights.
• Robust integrations with modern data ecosystems for data wrangling and analytics.

Ideal For:

• Organizations looking to automate and streamline their data analytics processes.
• Businesses that need a user-friendly data wrangling interface.
• Large enterprises requiring scalable solutions for complex data environments.

2. Talend

Talend is a leading open-source data integration and transformation tool. It offers a comprehensive suite of features for data wrangling, including data extraction, transformation, and loading (ETL).

It’s a browser-based platform with an intuitive point-and-click interface. It includes built-in processes for tasks like data enrichment and integration, and can connect with various enterprise systems.

Key Features:

• Supports various data sources and formats for unified data integration.
• Advanced data transformation capabilities.
• Seamless integration with cloud platforms.

Strengths:

• Highly scalable and flexible.
• Strong community support and extensive documentation.

Ideal for:

• Organizations seeking a versatile, open-source solution for complex data integration and transformation tasks.

3. Alteryx

Alteryx provides a data wrangling platform with powerful analytics capabilities. It can combine data preparation, blending, and analytics in a single workflow.

Alteryx has more than 100 pre-built data wrangling tools, covering everything from data profiling to find-and-replace and fuzzy matching. It offers broad support for various data sources while maintaining good workflow execution speed.

Key Features:

• Simplifies complex data workflows with its drag-and-drop interface.
• Integrates advanced analytics like predictive analytics and spatial analysis.
• Streamlines the data cleaning process through automated data preparation.

Strengths:

• Intuitive interface suitable for non-technical users.
• Deep feature set.

Ideal for:

• Businesses that need advanced analytics capabilities.

4. Altair Monarch

Altair Monarch is known for its data extraction and transformation capabilities. It allows users to easily convert unstructured data into structured formats.

The platform claims to extract data from multiple sources, including challenging formats like PDFs and text-based reports. Once extracted, Monarch processes the data according to your specified rules and directly inputs it into your SQL database.

It is particularly valued for its tailored solutions that cater to the reporting needs of the accounting and healthcare industries.

Key Features:

• Handles data extraction from PDFs, text files, and spreadsheets.
• Provides visual tools for data transformation.
• Integrates data from various sources into a single dataset.

Strengths:

• Excellent for extracting data from unstructured formats.
• User-friendly visual interface.

Ideal for:

• Users who need to extract and transform data from diverse and unstructured sources.

5. Datameer

‍

Datameer is a cloud-based data preparation and analytics platform that simplifies the data wrangling process with its intuitive interface and powerful features.

Key Features:

• Designed for scalability and flexibility in cloud environments.
• Intuitive visual data preparation for data transformation.
• Integrated analytics capabilities for advanced insights.

Strengths:

• Strong support for cloud environments.
• Seamless integration with big data platforms.

Ideal for:

• Organizations looking for a cloud-based solution with integrated analytics features.

6. Scrapy

Scrapy is a free, open-source data wrangling tool with a Python-based web scraping framework. It’s highly scalable, making it ideal for projects of any size. Its GitHub repository provides extensive code that allows users to customize and extend its functionality as needed.

Key Features:

• Extracts data from web pages and online sources.
• Supports various formats for exporting data, including CSV and JSON.
• Its extensible framework allows customization and extension through plugins.

Strengths:

• Ideal for web scraping and data collection from online sources.
• Highly customizable and extensible.

Ideal for:

• Users who need to extract data from websites and online sources.

7. Power Query

Power Query is part of Microsoft Excel and Power BI. While Power Query shares many ETL features with other data wrangling tools, its standout feature is its direct integration with Microsoft Excel.

This makes it the perfect choice for Excel users looking to enhance their data wrangling capabilities without stepping outside their familiar environment.

Key Features:

• Seamless data integration with Excel and Power BI.
• User-friendly interface with intuitive tools for data transformation.
• Connects to various data sources, including databases and online services.

Strengths:

• Excellent for users within the Microsoft ecosystem.
• Easy-to-use interface for data transformation tasks.

Ideal for:

• Users who require data wrangling capabilities within Microsoft Excel or Power BI.

Selecting the Right Data Wrangling Tool for Your Needs

When choosing a data wrangling tool, it’s essential to consider several key factors.

• Complexity of Data Sources: Some tools handle multiple types of data and formats better than others. If your data comes from many different sources, you’ll need a tool that specializes in consolidating and managing all these inputs effectively.
• Ease of Use: Think about how user-friendly the tool is. If you have non-technical teams working with data, look for a tool with a simple no-code interface. A more intuitive design will reduce the learning curve and make it easier for teams to use.
• Integration Needs: Check if the tool integrates well with your existing systems and platforms. A good data wrangling tool should connect smoothly with your current databases and software. This helps avoid disruptions and ensures all your data works together seamlessly.
• Cost: Evaluate the tool’s pricing structure. Some tools offer free versions with limited features, while others have more expensive plans. Choose a tool that fits your budget while still meeting your needs.

Take Action

Data wrangling tools are the go-to solution for growing organizations as data volumes increase, helping turn raw data into actionable insights while maintaining accuracy and consistency across operations.

Choose the right tools by assessing factors like data complexity, ease of use, integration capabilities, and cost. Making sure it aligns with your specific needs can enhance your data workflows and overall efficiency.

Take the first step now and try Savant for FREE to optimize your data processes and drive better business outcomes.