Transformation:
Unlocking the Value of Data

Data is only valuable if it can be used by the people and applications that need it. The challenge with spatial data is that, nearly always, "what they need" is not the same as "what we have". That's why data transformation is the key to any project that involves spatial data, ensuring successful data conversion, integration, and distribution.

Transformation is all about efficiently manipulating or restructuring data. It's a critical step in performing most data interoperability tasks, for example:

• Converting data between one or more formats
• Reprojecting data from one coordinate system to another
• Integrating data from multiple formats and sources
• Performing quality assurance or cleaning up data
• Loading or migrating data from one system to another
• Distributing data "on-the-fly", often via the web
• Extract, transform and load data into the desired format, data model and/or repository

Master more spatial data transformation challenges with FME

Transformation is where the true power and versatility of FME shine. Whether you are converting data within the same format, like Shapefile to Shapefile, or between data types, like CAD to GIS, FME gives you unlimited flexibility to restructure, manipulate, and integrate spatial data any way you need to. FME is built to make incoming data automatically meet the specifications of a destination format so that no data is "lost in translation". It also supports custom schema editing/mapping and includes a wide range of pre-built spatial and attribute transformations to help you unlock the full value of your data.

With FME, you can:

• Use an intuitive graphical interface to specify automatic, reusable data transformations – without coding
• Ensure accurate transformation by visually inspecting data before, during, and after conversion process
• Use FME's dynamic, on-the-fly data transformation capabilities to create a custom, self-service data upload, download, or delivery service

• Choose from a gallery of over 400 transformers to manipulate the structure and content of data as it moves from source to destination; for example:

  Transform data structures:

  • Add, remove, or rename attributes
  • Edit attribute data types
  • Merge and/or divide different data layers/classes
  • Join database attributes to feature geometry
  • Create mashups from multiple data sources and formats

  Transform data content:

  • Merge or split geometry or attribute values
  • Calculate new attributes from spatial operations and calculations
  • Clip and tile spatial data to predefined grids or boundaries
  • Overlay or mosaic data from multiple sources
  • Generalize, offset, rotate, warp, or reproject data