Best data preparation software of 2023

Data preparation software assists in the process of discovering, blending, combining, cleansing, enriching, and transforming data so large datasets can be easily integrated, consumed, and analyzed with business intelligence and analytics solutions. Data preparation tools provide IT departments, data analysts, data scientists, and average business users a platform to integrate disparate data sources in a quick and efficient way.

It makes for a much smoother analysis experience when businesses attempt to extract actionable insights from their data. Many data preparation solutions offer the functionality of data governance software, metadata management, and machine learning features. Data preparation is necessary to improve data quality.

Data preparation software is utilized by data-driven companies that empower their employees to explore business data to enhance decision making and drive productive change. Data preparation software integrates with analytics platforms and other analytics tools to clean datasets that can be easily understood and acted upon.

The integration with intelligence and analytical software helps in the actual analysis of the data. Data preparation tools may also be used in conjunction with data integration software to make it easier when combining data sources.

Best data preparation software

The best data preparation tools allow you to extract, transform and load your data while doing other important tasks like looking for duplicates, aggregating large volumes of data into more manageable chunks, and cleansing inaccurate or incomplete records. This comprehensive guide outlines the best data preparation software based on key features and usability.

Trifacta Wrangler

Trifacta Wrangler is a self-service business intelligence tool that helps data engineers, data analysts and data scientists to prepare and explore their data. The platform specifically allows users to transform data, ensure quality and automate data pipelines.

With Trifacta Wrangler, you can use a drag-and-drop interface to get your data into the right shape for analysis. This all-in-one platform enables users to merge and filter data sets, transform messy data into tables with readable formats, combine data sources and produce new records from existing ones.

Trifacta offers these three pricing plans: Starter, which is $80 per user per month with an annual contract; Professional, which is $4,950 per user per year; and Enterprise, with pricing information available upon request.

Features

• Active data profiling to automatically identify data set formats, schemas, specific attributes, relationships and related metadata
• Transform-by-example features for self-service data reformatting
• Machine learning guided interface
• Cluster standardization for comparable data sets
• Shareable recipes, macros, data flows and templates

Pros

• Graphical user interface that is easy to use and understand
• Low-code features for non-technical users
• Interactive platform format
• Easily integrates current processes with SDKs and OpenAPI standards in various languages
• Compatible with many different cloud data warehouse, data lake and lakehouse needs

Cons

• Slow platform speeds
• Inefficient data sampling method

Datameer

Datameer is a software-as-a-service data preparation and analytics platform that runs on Snowflake. It’s designed for business users, data engineers, analytics engineers, analysts and data scientists to prepare and analyze their data.

It combines the scalability, flexibility and power of cloud computing with a visual UI and robust features to simplify data preparation, visualization, exploration, cataloging and analysis. This solution allows practitioners to perform data cleansing, blending, grouping and organization, enrichment, transformation and validation at scale.

Datameer offers two pricing plans. The Personal plan is $100 per month for single users. Team pricing is available on-demand for prospective buyers that want to add multiple users.

Features

• Data blending using join and union functions
• Functions to build value-added columns, including math, statistical, trigonometric, mining and path construction
• Data grouping and organization feature for data classification and record aggregation
• No-code and low-code data transformation interfaces

Pros

• No-code analytics
• Easily connects to source data using connectors
• Allows collaboration between technical and non-technical teams
• Efficient, Excel-like interface
• Extensive data source connectivity
• Simple structured and unstructured data management

Cons

• Multiple tabs make it harder to focus
• Video lessons and tutorials are too long
• Visualization can be improved

Altair Monarch

Altair Monarch is a no-code, self-service data preparation solution that allows practitioners to access, clean, blend, combine, wrangle and append data to make data-driven decisions. It offers the benefits of an enterprise-level solution with the simplicity of a self-service tool.

Its powerful algorithms and automated data transformations can reduce the complexity in all stages of your analytics process, allowing for faster insights and better decision-making. In addition, this tool enables users to connect multiple data sources, such as structured and unstructured data, cloud data and big data.

Features

• Enables data extraction from PDFs, Excel workbooks, reports and web pages
• Built-in join recommendation intelligence and fuzzy matching feature
• 80+ pre-built data preparation functions
• Content server module allows users to organize, index, store, search, and retrieve text files and reports
• Automation and reusable workflows

Pros

• Allows users to automate recurring processes
• Feature-rich
• Easy to use
• Supports data extraction from various sources
• Enables users to transform locked and inaccessible data

Cons

• Installation guide can be improved
• Licensing fee

Alteryx Designer

Alteryx Designer is a powerful data preparation solution that allows you to work with your data in various ways. The software also offers an automated approach to preparing, cleansing and analyzing data sets.

Alteryx Designer allows you to analyze and transform structured and unstructured data from a variety of sources. It also provides multiple options for visualizing the prepared data, such as graphs, maps and heatmaps. In addition, the program helps users make sense of their data by using filters, tables and other interactive tools.

Features

• Aided modeling for end-to-end ML pipeline development
• SDKs for embedding the platform’s features into their applications, dashboards and workflows
• Compatible with semi-structured and unstructured sources, including PDFs, text files and images
• Visual canvas to document the analysis process

Pros

• Offers over 300 no-code, low-code automation building blocks
• Integrates with 80+ data sources
• Supports cloud, on-prem and hybrid deployment
• Automated analytics output to over 70 platforms

Cons

• Integration with the Google Cloud Platform can be improved
• Steep learning curve
• Users find this tool pricey

What is data preparation?

Data preparation, also called data cleansing or data wrangling, integrates and cleans raw data from different sources to enable downstream analysis, exploration and visualization. It is the process of extracting data from one or more data sources, transforming it into a clean, well-structured format, and then loading it into a target system.

Data preparation software is a solution that automates many time-consuming data prep tasks so analysts can spend more time asking questions and analyzing data. The demand for data preparation software solutions has increased as businesses store more unstructured data in databases, document management systems and other repositories while collecting additional types of structured and unstructured data from various sources.

Key features of data preparation tools

There are many different options for data preparation software on the market, and each solution offers its own unique functions and integrations. Here are some features to look for when deciding what software will work best for you:

• Visual interface: The visual interface is how users interact with the program. Depending on your data preparation needs, it’s important to find software with an easy-to-use and/or self-service interface.
• Easy integration: Integrating new data sets into your workflow is crucial for any data scientist or analyst who wants their research process streamlined. Look for tools that are compatible with many different data types and storage format types.
• Machine learning: You might also want to consider if the software offers machine learning capabilities like predictive analytics, which automate processes and help you to more easily keep track of your data.
• Collaborative editing: Sharing documents online has become increasingly popular. If you’re planning on collaborating with others on a project, select software that allows for document collaboration and role-based data sharing.
• Data governance: When working with sensitive information such as medical records, it’s essential to have strict data governance rules and regulations in place to designate who can access certain files and what they can do with them.
• Security: Data security should be a top concern for anyone purchasing data preparation software. Some providers offer end-to-end encryption and multi-factor authentication, while others integrate with top security solutions.
• Data extraction: Data preparation software should be able to extract information from various sources and formats, including PDFs, databases and spreadsheets. It should also have the ability to connect with other data sources to merge or compare data sets.

Why is data preparation important?

Data preparation is an integral part of the data analytics process. It can help you make sense of your data, making it easier to analyze and act. In addition, data preparation helps you to automate tedious and repetitive tasks, which can save your top data scientists and data engineers a lot of time and energy.