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Top 1 Data Preparation Software Companies With $1M–$5M Revenue (November 2026)

As of November 2026, Latka tracks 1 data preparation software companies with $1M–$5M in annual revenue. They have combined revenues of $2.2M and employ 20 people.

Every company below sells data preparation software to other businesses and is ranked by its most recent annual revenue. Revenue, funding, headcount and customer figures come from CEO interviews on the Latka podcast, public company filings, and Latka estimates where a company has not disclosed a number.

What Data Preparation Software Companies do

Data preparation software is designed to help organizations effectively collect, clean, transform, and organize raw data into a structured format suitable for analysis. This software plays a crucial role in ensuring data quality and usability, enabling businesses to derive actionable insights from their data analytics and machine learning initiatives. Typical use cases for data preparation software include preprocessing data for dashboards, reports, and data visualizations, as well as preparing datasets for machine learning and data science projects. Key features often include data cleansing, data transformation, data integration, and the ability to handle large volumes of unstructured data, making it accessible for further analysis by various stakeholders. Organizations from various sectors utilize data preparation software, with primary user personas including data analysts, data scientists, business intelligence professionals, and IT teams. These users rely on data preparation tools to simplify complex data workflows and automate repetitive tasks, ultimately fostering a data-driven decision-making culture within their organizations.

Companies
1
Revenue
$2.2M
Funding
-
Employees
20

Filters

Sorting: Highest -> Lowest

Filters

Top Data Preparation Software Companies With $1M–$5M Revenue

Showing 1 of 1 companies ranked by annual revenue.

1iterative.ai logo
iterative.ai

San Francisco, California, United States

We create open-source and SaaS developer tools dedicated to advancing machine learning data management. Our journey began with the creation of DVC, that is now an open-source standard for data versioning and reproducibility. Fast forward to today, we are launching DataChain. It is a multimodal data processing framework for ETL and data analytics at scale. 🌐 Enterprise Support Our team is dedicated to providing top-notch Enterprise support, ensuring your teams are set up for success. 💬 Let's Connect Curious to learn more? Schedule a 45-minute discussion with our experts to explore how Iterative can tailor solutions to your unique use case. Book a meeting here - https://calendly.com/dmitry-at-iterative/dmitry-petrov-30-minutes. 💡 Why Iterative We are on a mission to simplify the complexities of managing datasets and ML infrastructure. At Iterative, we bring the best engineering practices to data science and machine learning teams, empowering them to thrive in the ever-evolving landscape of Generative AI. Join us as we redefine possibilities and shape the future of Generative AI innovation.

Revenue
$2.2M
Year founded
2018
Team size
20

Frequently asked questions about Data Preparation Software Companies With $1M–$5M Revenue

How many data preparation software companies with $1M–$5M in annual revenue are there?

Latka tracks 1 data preparation software companies with $1M–$5M in annual revenue. Together they generate $2.2M in annual revenue and employ 20 people.

Which data preparation software company with $1M–$5M in annual revenue is the largest?

iterative.ai is the largest, with $2.2M in annual revenue, founded in 2018.

How much revenue does a typical data preparation software company with $1M–$5M in annual revenue make?

The average data preparation software company in this list makes $2.2M a year, across 1 companies with reported revenue.

Who are the leading Data Preparation software vendors with $1M–$5M in annual revenue?

Ranked by annual revenue, the leaders are iterative.ai.

Related IT Infrastructure Software categories

Inclusion Criteria

- The software must provide functionality for data cleansing and sanitization. - It should facilitate data transformation to make data analysis-ready. - Must support integration with multiple data sources and types. - The product should cater to both technical and non-technical users to enhance usability. - Not just data visualization tools; must also offer data manipulation and processing capabilities. - Should enable automation of data workflows to improve efficiency.