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See What’s New in Wrangler Pro & Enterprise

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April 9, 2018

This past Friday we cut a new release for Wrangler Pro & Enterprise customers so I wanted to walk through what’s new in the platform. Before I dive into the details, let me provide a little context on what guided our focus in this release.

As the data preparation market continues to grow and mature, the requirements of our customers have evolved. Core elements of our platform such as user experience, connectivity and machine learning are aspects of the product that we will continue to invest in with every release so no surprises with the enhancements we’ve delivered in those areas for this update. However, with this release, we’ve also expanded the platform’s capabilities in less obvious areas such as target-schema matching and dynamic operationalization that reflect how users are expanding upon their use cases and pushing us to deliver a broader set of capabilities in the platform. Capabilities that focus on repeated use and taking workflows that analysts may build in a dev or staging environment and providing a breadth of functionality that enable administrators to confidently deploy them in production….all within Trifacta.

Organizations aren’t just utilizing data preparation for ad hoc work with data, but rather leveraging data prep as a comprehensive platform for data analysts, data scientists and data engineers to collaboratively get data ready for use in an efficient, repeatable process. To meet these growing needs around operationalizing data preparation pipelines, we’ve added more flexibility in how users configure, schedule, manage and monitor repeatable workflows. Getting pulled in this direction by the market is a sign that a sea change in how this work is done is upon us.

At an initial glance, you may find that some of these new features resemble functionality of traditional data integration or ETL tools. But let me assure you that we’re not attempting to compete or replace ETL. However, as data preparation becomes a core process for how organizations more scalably prepare data for a variety of uses such as analytics, machine learning and data science, our product must be able to deliver the same production pipeline dependability of ETL products.

With that as background, here are some highlights of what’s new in Wrangler Pro & Enterprise:

  • Expanded Connectivity – a broader range of data sources are now supported as inputs and outputs of data preparation workflows. We’ve also added the ability for customers to develop their own JDBC connector or have us build on for them. Use the following links to view out the full range of connectivity for Wrangler Pro & Wrangler Enterprise.
  • Target Schema Matching – a lot of times our users need to take a variety of input data sources to meet a defined downstream data model or target schema. With this feature, users are able to continuously utilize the downstream schema format to inform and constantly validate their work during the development of their data preparation recipe.
  • Dynamic Datasets, Parameterization & Variables – users can utilize date/time parameters to define rules for executing data preparation workflows and outputs. Parameters allow scheduled job runs to pick up the right new data each time they execute.
  • New Workspace Navigation & User Onboarding – we’ve streamlined navigation across different elements of the product such as datasets, flows and jobs. The new release also features a brand new onboarding flow to guide new users and help them get productive quickly.
  • Transformation Discoverability – to help users more intuitively access the full range of transformation capabilities in the platform, we’ve added a new toolbar into the interface to more intuitively expose and organize main transformations.
  • Machine Learning – when bringing together disparate datasets, machine learning guidance is critical to identifying non-exact matching attributes across sources. With this update, we’ve expanded the auto-align functionality within Union to provide recommendations based on the content of the column vs. the column name. We’ve also brought data type standardization into the main transformation panel for easier access.
  • Expanded Cloud Deployment – we’ve already announced our relationship with Microsoft Azure and availability on the Azure Marketplace but with this release, we’ve expanded our support for Azure Active Directory, SSO and SAML.

Looking for more details on each of these new features? Over the next several weeks, we’ll have members of our product management and UX teams share detailed descriptions for all of the new functionality in the platform so keep an eye out for those posts.

Interested in getting your hands on the new release of Wrangler Pro & Enterprise? The best way to get started is to schedule a demo here.