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D s product
 enables you to explore, combine, and transform diverse datasets for downstream analysis.

Within the an enterprise, data required for key decisions typically resides in various silos. It comes in different formats, featuring different types. It is often inconsistent. It may require refactoring in some form for different audiences. All of this work must be done before you can begin extracting information valuable to the organization.


  1. Cut time to prepare actionable data

  2. Avoid IT bottlenecks and reliance on data scientists in data prep

  3. Deliver tools to prepare data to the people who understand the data

  4. Eliminate manual prep work

  5. Surface data quality issues in an interface a way that's easy to use to fix them

Featuring a leading-edge interface, powerful machine intelligence, and advanced distributed processing,

D s product
 renders the time-consuming, complex, and error-prone process of preparing datasets of any volume into a point-and-click exercise. What took six weeks in the IT lab can be done in less than two hours at the analyst's desk. Here is how. 


Did you know:

D s company
has been ranked the #1 vendor in Dresner Advisory Service's report on the data prep space in each of the last four years.


Additionally, customers may opt-in to share send anonymized usage data with to 

D s company
, so that the transformations being crafted across thousands of users can influence the machine-learning algorithms deployed in subsequent releases.


The scale and complexity of these transformations can quickly overwhelm even the most powerful of machines.

D s product
 utilizes a number of techniques to deliver high performance at scale.

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D caption
Platform interactions and data movements


When you finish your recipe, you run a job to generate results. A job executes your set of recipe steps on the source data, without modifying the source, for delivery to an a specified output, which defines location, format, compression and other settings.



For more information, see Overview of Target MatchingRapidTarget.


Getting Started

Overviews: Predictive Transformation | Sampling | Visual Profiling

Basics: Object Model | Import | Profiling | Transform | Running Job | Export