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Safer’s Tips & Tricks to Optimize 9 Favourite FME Transformers

Table of Contents
Level
Introductory
Broadcast
Wednesday, January 11, 2023
Presenters
Christian Berger
Dan Minney
Debbi Leung
Evie Lapalme
Jovita Chan
Nampreet Singh
Natalie Clouthier
Trent Kading

Webinar Details

The FME Transformer Gallery is vast, with over 500 different options to choose from. Often, knowing how to best make use of certain transformers can be a challenge. To ring in the New Year, our panel of support specialists will be taking you through their insider tips & tricks with their favourite transformers.

  • Natalie, the Creator: For when you just need that certain something to initialize an API call or test a workflow and take your workspaces to the next level.
  • Dan, the FeatureReader: Get more in-depth with your data reading. Flexible and dynamic workflows are about to become that much easier.
  • Trent, the AttributeRemove & Attribute Keeper : A 2-for-1 special with the trick to deciding when to use one versus the other to save you the most time.
  • Natalie, the Creator: For when you just need that certain something to initialize an API call or test a workflow and take your workspaces to the next level.
  • Chris, the AttributeManager: Ever wonder what it takes to be ranked the #1 FME transformer? Learn how this transformer, commonly referred to as the Swiss Army knife of transformers, is loaded with great features to help you simplify your workspace.
  • Jovita, the AttributeFilter: For all those times when you want to split up your data into a schema that fits your needs, whether you’re at the start of your workflow, or just about to write out at the end.
  • Nampreet, the FeatureMerger: An atypical, but useful, tip on how to use it to merge attributes without a common key attribute.
  • Debbi, the Counter: Not as simple as 1-2-3! Use this surprisingly versatile transformer to perform group counts and even count features at different parts of workspaces.
  • Evie, the Clipper: Clip anything from vector, rasters, and even point clouds. A simple trick of breaking down large datasets can drastically reduce memory usage when clipping!

Don’t miss the chance to join us & make it your New Years' resolution to whip your data into shape(files) with these 9 fantastic FME transformers.