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Top 3 Data Preparation Software Companies With $10M–$100M Revenue (November 2026)

As of November 2026, Latka tracks 3 data preparation software companies with $10M–$100M in annual revenue. They have combined revenues of $39.1M and employ 380 people. They have raised $133.1M and serve 500 customers combined.

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
3
Revenue
$39.1M
Funding
$133.1M
Employees
380

Filters

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Top Data Preparation Software Companies With $10M–$100M Revenue

Showing 3 of 3 companies ranked by annual revenue.

1Datameer logo
Datameer

San Francisco, California, United States

Datameer: Your Solution to Self-Serve Data Analysis and Visualization. Empower analysts with a comprehensive platform for data preparation, cleaning, combining, and organizing, seamlessly integrated with Snowflake, to unlock actionable insights for better decision-making and unleash the full potential of your data. Headquartered in San Francisco, California, Datameer has a global presence with offices in key locations around the world. The company serves customers across various industries, including finance, healthcare, telecommunications, retail, and more. Its versatile platform caters to organizations of all sizes, ranging from small startups to large enterprises, and is used by data scientists, analysts, and business users alike. Over the years, Datameer has built a strong customer base, with thousands of satisfied customers across the globe. Its innovative data analytics platform has helped numerous organizations unlock the value of their data, driving improved operational efficiency, better customer insights, and increased revenue. Datameer's commitment to providing cutting-edge data analytics solutions has earned it a reputation as a trusted partner for businesses seeking to harness the power of data to gain a competitive advantage in today's data-driven world. Datameer works with customers from every industry including Dell, Vodaphone, Citibank, UPS, and more.

Revenue
$17.6M
Year founded
2009
Team size
160
2Flatfile logo
Flatfile

Denver, Colorado, United States

Flatfile’s vision is to enable seamless data exchange between companies — large and small — throughout the world. With AI-assisted data exchange, Flatfile eliminates repetitive work and makes B2B data exchange fast, intuitive, and error-free. The Flatfile platform automatically learns how imported data should be structured and cleaned, enabling customers and teams to spend more time using their data instead of fixing it. Flatfile has completed over 25 billion data mapping decisions for companies like Sage, ClickUp, Square, AstraZeneca, CBRE and Spotify. For more information, email [email protected] or visit flatfile.com.

Revenue
$10.9M
Customers
500
Year founded
2018
Funding
$94.6M
Team size
65
3Prophecy.io logo
Prophecy.io

San Diego, California, United States

Prophecy is a cloud-based data engineering platform that allows data teams to easily collect, transform, and integrate data from various sources. It offers a range of features such as data pipelines, data validation, version control, and monitoring to streamline the data engineering process. The company is headquartered in San Francisco, California and was founded in 2017.

Revenue
$10.6M
Year founded
2017
Funding
$38.5M
Team size
155

Frequently asked questions about Data Preparation Software Companies With $10M–$100M Revenue

How many data preparation software companies with $10M–$100M in annual revenue are there?

Latka tracks 3 data preparation software companies with $10M–$100M in annual revenue. Together they generate $39.1M in annual revenue and employ 380 people.

Which data preparation software company with $10M–$100M in annual revenue is the largest?

Datameer is the largest, with $17.6M in annual revenue, founded in 2009.

How much revenue does a typical data preparation software company with $10M–$100M in annual revenue make?

The average data preparation software company in this list makes $13M a year, across 3 companies with reported revenue. They serve 500 customers combined.

Who are the leading Data Preparation software vendors with $10M–$100M in annual revenue?

Ranked by annual revenue, the leaders are Datameer, Flatfile and Prophecy.io.

How much funding have data preparation software companies with $10M–$100M in annual revenue raised?

The 3 data preparation software companies with $10M–$100M in annual revenue tracked here have raised $133.1M in disclosed funding between them.

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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.