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How Trifacta, DataRobot, and AWS help Consensus Corporation wrangle data for use in machine learning models that predict fraud activities

Data wrangling (that is, preparing data to be ingested by machine learning algorithms and analytics) regularly takes up to 80% of a data scientist’s time. Automating your data wrangling tasks and machine learning modeling can lead to greater data accuracy and more meaningful insights, while freeing your teams from the repetitive and risky manual tasks associated with data preparation.

Trifacta, built on Amazon Web Services (AWS), and DataRobot allow your data science and data analysts teams to spend less time preparing and modeling data for machine learning, and more time developing models that benefit your organization.

Trifacta can help you:

  • Make data preparation 10 times faster so that your data professionals can automate predictive modeling and manage more machine learning initiatives.
  • Empower people who know the data best, but who do not necessarily have the time or technical expertise for traditional data preparation tasks.
  • Turn customers into data-driven organizations with more efficient business processes and more-informed data-driven prediction engines.

Read the Consensus case study.