how to efficiently transform non-spatial data using fme
DESCRIPTION
FME supports a wide range of non-spatial data, from spreadsheets (CSV, Excel) to databases (SQL Server, Oracle) and to key applications (Salesforce, Socrata). In this webinar, discover how to easily transform non-spatial data for use, even adding a spatial component to your non-spatial data. You'll also hear how SYNCADD has been using FME to solve non-spatial challenges in a variety of situations.TRANSCRIPT
How to Efficiently Transform Non-Spatial Data using FME
March 13, 2013
Who Are We?
Dale LutzCo-Founder andVice President of DevelopmentSafe Software
Aaron KoningFME Server Product ManagerSafe Software
Daniel RiddleGIS Specialist for SYNCADD Systems Inc.
Kristofor CarleSoftware Developer for SYNCADD Systems Inc.
Guest Speakers
Questions are Encouraged!
This morning’s Q&A Support:
Mark StoakesManager Professional Services Safe Software
Iris Gutowski Product Support Specialist Safe Software
Powering The Flow of Spatial Data
FME – Feature Manipulation Engine
Powering The Flow of Data
FME – Feature Manipulation Engine
FME Capabilities
Transform Data to Use and Share
Convert spatial data between hundreds of formats
Transform spatial data into the
precise data model you need
Integrate multiple different data types into a single data model
Share spatial data with people where, when and how they need it
Workbench: Graphical Data Flow Authoring
Getting started page:
http://fme.ly/GetStarted
Attend a weekly FME Desktop overview webinar:
http://fme.ly/WeeklyIntro
New to FME?
Poll: How much of your data is Non-Spatial?
Beats Writing Code Easier to maintain Faster to configure
Powerful Transformations and Filtering
Supports Most Common Formats
Consistent Handling of Spatial and Non-Spatial in one tool
Why FME for Non-Spatial?
Spatializing Transformers
Spatializing Transformers
FME Supported Formats
Poll: What Non-Spatial Formats are of most interest to you?
1 - Old School Non-Spatial
Egg Information (CAT)NEST_ID EGG_ID DATE_LAID DATE_HATCHED INCUBATION_DAYS 20 0 20040819 20040826 7 20 1 20040823 20040829 6 20 2 20040818 20040826 8…
Species (CSV)NestId,Species100,BLUE JAY101,AMERICAN GOLDFINCH…
1 - Old School Non-Spatial
Create a DBF file of: Number of Eggs Average Incubation
… for each species of bird
DEMO
2 – The Office
2 – The Office
Reorganize the Vancouver Business Licenses Excel File Separate tabs for license state Create summary tab Flag errors into a new file
DEMO
3 – Hipster
3 – Hipster
3 – Hipster
3 – Hipster
Check if my electric car needs charging Read the Tesla Vehicle Webservice (which returns JSON) Explode the JSON Check if charging needed
Send email if yes Honk horn if NO
DEMO
4 – Corporate
4 – Corporate
Update Oracle with results from complex MS SQL Server query
DEMO
5 – Cloudy
5 – Cloudy
Publish data from SalesForce to Socrata Filter out bad data along the way Plus do schema restructuring for data
sharing
DEMO
Daniel RiddleGIS Specialist for SYNCADD Systems Inc.
Kristofor CarleSoftware Developer for SYNCADD Systems Inc.
Guest Speakers
Story 1: Data Upload Monitoring
• The Mission: Monitor data uploaded via a web interface to an Army Geospatial Data Warehouse for compliance and data model validation, reporting the results.
• The Solution: Use FME Server and custom transformers to run QA tests and email the results as Excel spreadsheets.
SYNCADD
• Custom transformers are created and source user parameters are published to leverage FME Server.
• Readers Used: Schema; ESRI Personal, File, & SDE Geodatabase
SYNCADD
Custom transformers complete various tests on metadata tags, schema feature classes, and schema attributes.
SYNCADD
Results are exported as Microsoft Excel spreadsheets and emailed to the user using FME Server.
• The Mission: Evaluate, document, and reproduce a non-spatial ETL process currently maintained in MS Access so that business experts (not just data analysts/DBAs) can understand it.
• The Solution: Use FME to reorganize the process into diagrams in custom transformers. Add visual QA/QC checks directly into the workflow.
Story 2: Non Spatial MS Access ETL
SYNCADD
• Before: SQL queries in MS Access
SYNCADD
• After: FME creates a diagram that is easy to understand.
SYNCADD
• Inspection points and FME Data Inspector make it easy to evaluate the process even on the fly in a meeting.
• Visually compare link counts on printed diagrams after each data import to look for possible problems.
SYNCADD
Don’t let the Spatial scare you off!
FME is a powerful Non-Spatial problem solving machine
FME is not just for the desktop FME Server is engineered for enterprise data
transformation Automate your non-spatial workflows
Summary
2013 FME World Tour!
40+ FME User Meetings happening world wide and one live stream
Register atwww.safe.com/worldtour
Upcoming webinars
How to Easily Read and Write CityGML Data Using FME – March 27
How to Load Spatial and Non-Spatial Data into Terdata using FME – April 3
PostGIS 2.0 – How to Improve Interoperability using FME – April 24
Recorded Webinars: http://fme.ly/webinars
View the offerings at: http://fme.ly/online
Poll: Would you like more information on our free training options?
We’ll Be Following Up
Thank You!
For more information, contact: Sales
[email protected] Support
[email protected] (604)501-9985 ext. 278
Aaron [email protected]
Dale [email protected]
Daniel [email protected]
Kristofor [email protected]