Trifacta Expands Data Wrangling on the Cloud with Additional Support of Amazon Web Services and Availability on AWS Marketplace

Print Friendly, PDF & Email

Trifacta, a leader in data wrangling, announced expanded support for Amazon Web Services (AWS) and the availability of Wrangler Edge and Wrangler Enterprise on AWS Marketplace, allowing organizations to deploy Trifacta in less than an hour. Trifacta has also earned AWS Machine Learning (ML) Competency status. This achievement recognizes that Trifacta has demonstrated success in helping customers deploy their ML workloads on AWS.

Clean and annotated training data is the foundation of modern machine learning,” said Joseph Spisak, Global Lead for Machine Learning Partnerships, Amazon Web Services, Inc. “It fuels state of the art algorithms in computer vision and natural language understanding. However, acquiring clean and annotated training data takes time and resources. We are very excited to have Trifacta join the Machine Learning Competency Program to help our customers spend less time preparing their data and more time creating intelligence.”

A growing number of organizations are transitioning their data management workloads to the cloud for greater flexibility and improved efficiency. Wrangler Edge and Wrangler Enterprise provide an intuitive, efficient way for teams and organizations to wrangle data across AWS services, including Amazon Simple Storage Service (Amazon S3) and Amazon Redshift for ML and visualization in applications including Amazon QuickSight:

  • Wrangler Edge enables teams and departments to quickly start wrangling data on the cloud. With pricing available either per-hour or as an annual subscription and one-click deployment on the AWS Marketplace, users can be up and running on Wrangler Edge in under an hour.
  • Wrangler Enterprise supports large-scale data wrangling initiatives that require more powerful computing such as the parallel processing power of Amazon EMR. Wrangler Enterprise on AWS provides support for customers wanting to wrangle raw data stored in Amazon S3 for downstream analysis in Amazon Redshift.

At Malwarebytes, our team analyzes a constantly growing variety of data when creating a multi-layered defense in depth strategy to defeat the latest, most dangerous malware. Our engineers work with data every day, but the time-consuming work of wrangling by hand hurts overall productivity,” said Manjunath Vasishta, Director of Data Science and Engineering, Malwarebytes. “With Trifacta deployed on AWS, our data analysts and engineers are able to more efficiently access and wrangle diverse data stored across various AWS services such as Amazon S3 and Amazon Redshift while also benefiting from the agility the cloud provides. The speed at which we’re able to break down raw log data into usable information to improve our products has accelerated dramatically with Trifacta.”

As part of Trifacta’s enhanced support for AWS, Trifacta has also collaborated with partners Infosys and FICO to bring their analytics offerings to AWS. Trifacta is the data wrangling solution within the Infosys Analytics Workbench, which means that Infosys customers can now leverage Trifacta to support end-to-end deployment on AWS. FICO Decision Management Suite is a leading solution for developing and operationalizing analytic and decision models. Available on AWS, the FICO Decision Management Suite leverages Trifacta as the data wrangling solution for customer implementations.

More and more Trifacta customers are leveraging AWS for their data management needs, including Consensus Group, Malwarebytes, NationBuilder and OpenGov,” said Adam Wilson, CEO, Trifacta. “Our expanded collaboration with AWS and deep integration with AWS services will automate how organizations refine raw data to accelerate analysis and improve machine learning. Trifacta’s data wrangling services attack the data preparation bottleneck by enabling analysts, data scientists and engineers to explore, clean, and blend data visually, on their own, so they can spend more time on the analysis and less time writing code, or implementing complex, expensive ETL processes.”


Sign up for the free insideBIGDATA newsletter.


Speak Your Mind