8 Essential Data Wrangling Tools For Efficient Data Analysis

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

Pricing

• 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.

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

Pricing

• 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.

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

Pricing

• 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.

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

Pricing

• 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.

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

Pricing

• 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.

6. Tableau

Pricing

• 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.

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

Pricing

• 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.

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

Pricing

• 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.

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.

Conclusion

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.