Jeff DeWitt, a GIS Administrator with Georgia Power's Community and Economic Development group, will present several different situations where he uses FME to automate and solve everyday problems including several non-spatial problems.

1. The Automator
Jeff DeWitt
Georgia Power Community &
Economic Development

2. About Us
Jeff DeWitt – The Automator
GIS Administrator
Georgia Power
Community & Economic Development

3. FME is a
fantastic tool
to automate
everyday tasks
Examples
• Location Comparisons
• Site Analysis
• Site Update Emails

4. Location Comparisons
Before - text files, spreadsheets

5. Location Comparisons
Key Transformers
• RegEx Tester – used to isolate
specific lines of data in text files,
i.e. ^([A-Z])(.+)
• StringReplacer – removed
unwanted text/characters
• FeatureMerger – appended data
to a feature (table row)
• AttributeValueMapper – used for
field mapping to get features
from different sources to match
Created 17 different workspaces, one for
each source

6. Location Comparisons
After – Access DB, Report

7. Location Comparisons
Summary
• Converted many non-spatial files into Access database
• Standardized names, data
• Rolled up data by MSA
• Automated entire process of creating location comparisons saving
hours of work compiling data and ensuring data accuracy

8. Site Analysis
Before – county parcels

9. Site Analysis
Key Transformers
• NeighborFinder – used to find
nearest facilities/utilities
• Clipper – calculated usable acres
(parcel minus wetlands/floods)
• SpatialRelator – determined if
features intersected each other
• FeatureAdder – great way to add
only features that need to be
evaluated (streams, wetlands,
floods)

10. Site Analysis
After – parcel score layer,
Access DB

11. Site Analysis
Summary
• Largely a spatial analysis program
• A final score for each parcel was calculated using many criteria
including distance to transportation, usable acres, and availability
of utilities
• Automated process of evaluating potential economic development
sites in an objective, fast, and accurate manner saving hours of
work compiling data and ensuring data accuracy

12. Site Update Emails
Before – economic development sites
with outdated data, manually send
emails to update site data

13. Site Update Emails
Key Transformers
• DateDifferenceCalculator – used
to find sites that have not been
updated in last year
• XMLTemplater – formatted email
using HTML
• HTMLPythonEmailer – sends all
sites for each contact in site
database with customized
greeting and content

14. Site Update Emails
After – customized email
with site information and
aerial image

15. Site Update Emails
Summary
• Reads feature class from SDE Oracle database and sends filtered
records via email in a format the site representative can easily
update and return
• Automated process of contacting each site representative saving
tedious process of compiling data and sending many emails
• Process has resulted in a higher percentage of sites updated within
the past year

16. Thank you!
Jeff DeWitt
Georgia Power
Community & Economic Development
jldewitt@southernco.com
404-506-4054