Democratized data preparation by enabling users to transform raw data into analysis-ready formats through an intuitive, AI-powered interface that reduced the time and technical expertise required for data wrangling.
Last updated Feb 8, 2026
- Business Model
- SaaS
- Target Market
- Enterprise
- Employee Count
- 201-500
- Funding
- $176.5M
- Revenue Range
- $10M-$50M
- Stock Symbol
- NASDAQ:TRIF
- Parent Company
- Alteryx
- API Available
- Yes
Market Position
Leading data wrangling platform acquired by Alteryx to enhance analytics automation capabilities
Overview
Trifacta was a data wrangling and preparation software company, not an AdTech company. It developed cloud-native platforms that helped data analysts, scientists, and engineers transform raw, messy data into clean, structured formats suitable for analysis. The company's solutions leveraged machine learning and intelligent suggestions to automate and streamline the data preparation process, making it more accessible to users without extensive coding skills. Trifacta was acquired by Alteryx in January 2022 for approximately $400 million, integrating its data preparation capabilities into Alteryx's analytics automation platform. While Trifacta's technology could be used by companies in various industries including those in advertising and marketing for data preparation tasks, it was not specifically an AdTech platform and did not operate within the advertising technology ecosystem as a core business.
Products & Features
Trifacta Wrangler
Cloud-based data preparation platform for transforming raw data into structured formats
Trifacta Photon
Execution engine for processing large-scale data transformations
Trifacta Data Preparation for Cloud Dataprep
Google Cloud-native data preparation service powered by Trifacta technology
Key Features
Machine learning-powered data transformation suggestionsVisual data profiling and quality assessmentCollaborative data preparation workflowsAutomated data cleansing and standardizationSupport for structured and unstructured data
Use Cases
Data preparation for analytics and BIData quality improvementETL/ELT pipeline developmentSelf-service data preparation for analystsData lake preparation
Customer Segments
Enterprise data teamsData analystsData scientistsBusiness intelligence teamsData engineers