8 Essential Data Wrangling Tools For Efficient Data Analysis

Reading time: 10 min read
Written by

Updated · Jul 31, 2023

Joined April 2023

With more than five years of experience in the background check industry, Ritesh Kumar founded Looku... | See full bio

Florence Desiata
Edited by
Florence Desiata


Florence Desiata
Joined June 2023 | LinkedIn
Florence Desiata

Florence is a dedicated wordsmith on a mission to make technology-related topics easy-to-understand.... | See full bio

Techjury is supported by its audience. When you purchase through links on our site, we may earn an affiliate commission. Learn more.

Data wrangling (also called munging) makes raw data easier to work with. It involves cleaning up data, transforming it into a suitable format, and organizing it for analysis.

This process can be manual or automated to handle today’s growing data.

Data wrangling tools play a crucial role. These tools help automate repetitive tasks such as data cleaning and merging. It saves time and reduces the chances of error.

If you’re looking for data-wrangling tools for your data analysis projects, this article is for you. Read on.

Data Wrangling Tools

Data wrangling tools make identifying patterns, spotting anomalies, and uncovering meaningful insights hidden within the data easier. They give analysts the ability to handle complex data more efficiently.

Here are eight tools used for data wrangling:

1. Talend



  • 14-day free trial
  • $1,170 per month
  • $12,000 per year

Key Features

  • Flexible data pipelines: When creating data pipelines, Talend surpasses limitations by platforms or vendors. It empowers users to build pipelines from integrated data and allows them to run them anywhere.
  • Data quality management: Talend incorporates advanced machine learning capabilities to enhance data quality. It automatically purifies ingested data by performing tasks such as deduplication, validation, and standardization.
  • Universal data integration: This data wrangling tool can handle any data from various sources. It provides seamless integration capabilities regardless of the data location.



  • Provides multiple open-source integration tools at no cost 
  • Reduces data handling time, allowing developers to complete tasks in half the time.
  • Can handle complex data transformations and manipulations easily
  • May crash when dealing with vast amounts of data
  • Does not provide practical ways to perform unit testing of the components
  • May not always meet the requirements for more complex tasks

Talend is a user-friendly data wrangling tool for data preparation, cleaning, and manipulation. It offers a browser-based platform with a simple interface. 

Users can easily apply rules to datasets, share them with teams, and integrate them with various enterprise systems.

This tool supports code-based customization and built-in Extract, Transform, and Load (ETL) capabilities. It’s suitable for beginners and experienced users alike.

Talend uses machine learning algorithms for cleaning and transforming data. It provides automated recommendations and governance features. This tool also allows for easy sharing and integration of data preparations.

2. Alteryx



  • Free trial
  • $5,195 per year

Key Features

  • Collaborative data exploration: Alteryx enables users to search for any data asset and collaborate. This allows them to work together to create new analytics tools and leverage models created by others.
  • Comprehensive data preparation: This tool offers powerful data preparation capabilities. Users can easily clean, transform, and manipulate their data to ensure it is in the desired format for analysis.
  • Sharing and collaboration: Alteryx encourages users to share their knowledge and tools with the community. They advocate for the complete disclosure of information and analytics tools the community produced.



  • Allows users to view and manipulate data while in the process
  • Has a drag-and-drop tool, making it easy to learn the software quickly
  • Can be expensive due to its costly license-based pricing model

Alteryx is a powerful data wrangling tool that combines data profiling, analytics, and data science capabilities in one place. It offers over 100 pre-built tools for tasks like find-and-replace and fuzzy matching.

This tool has an intuitive interface, allowing users to connect and clean data from multiple sources. It includes spreadsheets, mobile apps, social media, and others.

Alteryx outperforms MS Excel when working with large datasets and seamlessly integrates with other tools for data visualization. It also supports blending spatial data files with third-party data like demographics for more comprehensive analysis.

3. Altair Monarch

Altair Monarch


  • 30-day free trial
  • $1,995 per year
  • Altair Monarch Server starts at $10,000

Key Features

  • PDF importing: This data wrangling tool allows users to import PDF files and extract tables from text-heavy documents. Users can modify the tables and align text within grids by identifying graphical features on the PDF page pictures.
  • Integrations: Altair Monarch provides seamless integration with various data sources. This includes OLEDB/ODBC systems, data models, flat files, workspaces, relational databases, web inputs, and multi-structured data sources.
  • Data export: This tool enables users to export data in multiple formats (CSV, JSON, MS Access). It also allows users to export data directly to different platforms for further analysis and visualization.



  • Automates data transformation tasks 
  • Easy-to-use interface and over 80 pre-built functions
  • Employs a robust data processing engine to deliver efficient handling of large datasets
  • Does not provide comprehensive data security and governance features
  • Unable to extract data from scanned documents
  • Requires training to utilize its advanced capabilities fully

Altair Monarch helps make complex and unstructured data easier to understand and work with. It is known for extracting various sources, including challenging formats like PDFs and text-based reports.

With Altair Monarch, you can define rules to transform the data and directly insert it into your Structured Query Language (SQL) Database.

This tool provides many functionalities, with over 80 pre-built data preparation functions. These functions cover a variety of tasks needed for data transformation.

4. Datameer



  • Free trial
  • Personal: $300 per year
  • Workgroup edition: $19,188 per year

Key Features

  • Substantial documentation: Datameer lets users create and access system-generated and user-generated data documentation. This includes metadata and wiki-style descriptions, comments, and tags.
  • Multiple user environments: This tool offers different environments for data transformation. It caters to both tech-savvy individuals and non-technical users.
  • Shared workspace: Teams can collaborate and reuse models in Datameer, enhancing productivity and accelerating project timelines.



  • Easy to use with its no-code interface
  • Low cost compared to similar tools
  • Has excellent enterprise support for workflows and advanced analysis
  • Has limited capabilities in data visualization
  • Needs more information in its training materials

Datameer is a tool designed to help software engineers with data wrangling and integration. It is a Software-as-a-Service (SaaS) platform that simplifies the instruction, manipulation, and loading of datasets into cloud data warehouses.

This tool allows users to input data in various formats, such as CSV and JSON, and perform aggregation on the datasets. It includes catalog-like data documentation, comprehensive data profiling, and discovery.

Datameer operates on a scalable data warehouse and utilizes efficient data stacks and functionalities similar to those found in Excel to transform data. 

These transformations enable users to derive meaningful insights from the data for analysis and decision-making purposes.

5. Microsoft Power Query

Microsoft Power Query


  • Free add-in on Excel 2010 and 2013

Key Features

  • Simplified data combination: With Power Query, you can easily combine tables and merge datasets. This eliminates the need for complex formulas like Excel’s VLOOKUP function. 
  • Data source connectivity: This tool simplifies importing data from diverse sources, such as text files, CSV files, and Excel Workbooks.
  • Efficient data replication: Power Query helps in regularly importing changes from the same data source. If you need to import updates frequently, it automates the process and reduces the need for manual data replication.



  • Simplifies tasks like deleting unnecessary rows and changing data types
  • Remembers the transformation steps, allowing quick updates without starting from scratch
  • Offers connectors for various data sources, including SQL databases, web pages, cloud storage, and local files
  • Might not be the best choice if you don’t utilize Microsoft software like Power BI and Power Automate 
  • May cater to something other than advanced data wrangling needs that require coding

6. Tableau



  • Free trial
  • $70 per month

Key Features

  • High security: Tableau Desktop ensures data security through multiple authentication techniques and authorization systems. It supports security protocols and employs cryptographic processes for secure communication.
  • Visually appealing: This tool creates visually appealing and interactive reports. It makes the data wrangling process more precise and more engaging.
  • Real-time sharing: Tableau enables users to share reports, workbooks, and data visualizations in real-time with teammates or other users. This promotes efficient collaboration and faster decision-making within the business.



  • Offers a mobile app for iOS and Android
  • Has a drag-and-drop functionality, making data visualization easier
  • Smooth upgrades
  • Requires manual update when data changes
  • Revision history is only available in recent versions 

Tableau, a data visualization tool, allows you to create visually appealing and interactive reports.

With Tableau, you can preview your data quickly and easily in a data preview window. This feature allows you to see the critical elements of your dataset at a glance. It makes it easier to understand its structure and content.

Tableau’s data prep functionality is less extensive than other dedicated data wrangling tools.

However, despite its limitations in data wrangling, Tableau shines in creating captivating reports and dashboards. It provides a visually rich and interactive environment that makes data exploration and analysis more engaging and enjoyable.

7. R



  • Available for free

Key Features

  • Cross-platform support: R can run on different operating systems (Windows, MacOS, Linux). It is also compatible with other programming languages, facilitating collaboration when dealing with computationally heavy tasks.
  • Rich set of packages: R provides data engineers access to over 10,000 standardized packages and extensions from the Comprehensive R Archive Network (CRAN).
  • Extremely powerful: This data wrangling tool has distributed computing packages that enable it to handle complex and straightforward dataset manipulations.



  • Supports various machine learning operations
  • Provides packages for developing artificial neural networks
  • Open-source language
  • Has over 10,000 packages in the CRAN repository for data science and machine learning operations

  • Stores objects in physical memory. consuming more memory 
  • Less ideal for handling big data

R is a powerful tool for handling and analyzing data in various fields. It is designed specifically for statistical computing and graphics.

This tool consists of a programming language and an environment. The language itself is used to write scripts and commands to manipulate data. 

It provides various statistical techniques, clustering, classification, and data analysis functions.

The R environment provides a collection of software packages that extend the functionality of the language. These packages offer additional tools and functions for data visualization, manipulation, import/export, and more.

8. OpenRefine



  • Available for free

Key Features

  • Rich set of APIs: OpenRefine offers various APIs, including OpenRefine API, data extension API, and reconciliation API. This enables users to interact with data and extend the tool's functionality.
  • Clustering: This tool provides clustering capabilities that allow users to find similar but not identical entries in the data. This feature helps clean up large datasets efficiently.
  • Unlimited undo and redo: OpenRefine enables users to undo any actions that modify the data. It keeps a record of all changes made to a project, enabling users to track and review past edits quickly.



  • Lets users perform advanced data transformations 
  • User-friendly interface without a programming language
  • Supports importing data from CSV, TSV, JSON, XML, and more 
  • Workspace directories are locally stored, ensuring data is not copied to remote servers
  • Does not have official technical support available
  • Can be constrained by computer processing power and local memory

OpenRefine is an open-source tool that helps you clean and organize messy data. It is designed to quickly explore datasets and transform the data into the desired format.

This tool allows you to apply complex transformations to individual cells in your dataset. It uses filters and partitions to sort and filter your data.

OpenRefine works with data wrangling projects, allowing you to work with datasets from web URLs, computer files, and databases. You can easily pull these datasets into your project and work on them locally on your machine.

Importance Of Data Wrangling

Data wrangling is essential for several reasons:

  • Making raw data usable

Data wrangling ensures raw data is cleaned, transformed, and structured to be effectively used for downstream analysis. 

This guarantees that high-quality data is entered into the analytical process. It leads to more accurate and reliable results.

  • Centralizing data from various sources

Data wrangling involves gathering and bringing data from varying sources to a centralized location. This allows for easier access and integration of data.

  • Standardizing data for cross-data set analytics

Automated data integration tools used in data wrangling help clean and convert source data into a standardized format. 

It can be used consistently across different datasets. This standardization enables businesses to perform crucial cross-data set analytics.

  • Cleaning data from noise and flaws

Data wrangling helps identify and remove noise, errors, and missing elements from the data. The resulting clean data provides a more reliable basis for analysis and decision-making.

With proper data wrangling, the integrity and reliability of the analysis can be maintained. This may lead to missed opportunities and flawed models that harm the organization’s reputation.


Data wrangling is about preparing and refining data for analysis. Tools for this process offer features like data visualization, data quality checks, and data integration. These allow efficient handling of complex data while saving time by automating repetitive tasks.

When choosing a data wrangling tool, select what fits your needs, preferences, and budget.


Is SQL used for data wrangling?

Yes, SQL is commonly used for data wrangling tasks. SQL commands allow you to manipulate and transform data from various sources, like CSV files, web services, and databases.

How to do data wrangling in Excel?

Data wrangling in Excel involves three standard methods. This includes removing extra spaces with the TRIM function, finding and replacing texts, and distributing cell contents to adjacent columns.


Facebook LinkedIn Twitter
Leave your comment

Your email address will not be published.