This document discusses how raw data can be transformed into business information. It describes the process of collecting, processing, and analyzing data from various sources to create structured information that can be reported and distributed. Various techniques and products are used, including BPMN for process modeling, FME for extract-transform-load tasks, PostgreSQL with PostGIS for the data warehouse, and QlikView for analytics and reporting. FME is highlighted as a powerful tool that can integrate different data types and sources, perform quality checks and enhancements, and distribute data to the appropriate systems and formats.

1. Transforming Raw Data
into Business Information
Luc Janssens
Data-, -Analysis- & GIS-coördinator
Department Managementconsulting & Projectmanagement
City of Lier, Belgium

2. 1: Data, Information & intelligence

3. Operational Environment
– Non- or thematically structured data
Data
– Structured collection of data
Information
– Structured presentation of data
Intelligence
– Data within a business / mutual context

4. Operational environment
= Non- or thematically structured data
Knowledge
– What people know
– Dataflow model (creation and maintenance)
– BPMN as notation formalise processes
– Empowerment of the specialist in order to make his expertise
accessible and reusable
Cabinets
– Clean-up, digitize, archive
– Create re-usable indexes (meta-data) or digitize paper
documents into reusable repositories.
Computers
– A mix of formats, applications, open or closed, structured or
plain garbage.
– External & Internal sources, applications, acces-rights
– Quality = timely, complete, accurate, consistent, well-defined,
unique
– Meta-Data describes data-quality

5. Data
= Structured collection of data
Data-Collection
– Collect data from different sources
Data-Processing
– Processing: Convert data into the desired data-model
– Cleaning: Erroneous, irrelevant, redundant or incomplete data
– Exploitation: Publish data for the desired target systems
Data-Needs
– WHAT… do we want to manage, analyse, report upon, alarm upon,…
– In which form should we do this?
– Business WareHouse: Unique data-model for reporting
– MasterData: Specific model for cross application exchange
– Location WareHouse: Add location based intelligence

6. Information = Structured presentation, reporting en distribution
of data.
Information
– Who, What, Where, When, Why and How?
– In what form? Automatied, distribution to other systems and/or
organisations, BI, Reporting, Paper-output, GIS, …
Analysis & Production
– Descriptive/post/pre-emptive statistics as automated intelligence
– Data-visualisation en data-exploration as manual intelligence
Intelligence
– Data in a mutual context
– Focus on the essential within a specific context
– Collaborate within a specific context
– Alarming & Dashboards

7. 2: Techniques & Products.

8. Technological choise
BPMN
ETL
RDBMS
BI
BI Reporting
QlikView & GeoQlik
nPrinting
Bizagi
FME
PostGreSQL & PostGIS

9. BPMN Business Proces Model & Notation
Bizagi Modeler
www.bizagi.com

10. ETL Extract – Transform - Load
FME Desktop
www.safe.com

11. Statistieken
Meta-Data
1 Central Data-Warehouse (Business – MasterData – Location)
Central Data-Warehouse
PostGreSQL PostGIS
www.postgresql.org www.postgis.net

12. Data-Analysis / Dashboards / Collaboration
QlikView GeoQlik
www.qlik.com www.geoqlik.com

13. Data-Reporting / Distribution
QlikView nPrinting
www.qlik.com www.qlik.com

14. 3: FME Usage and advantages.

15. Scripting / Shapeloader / SQL / …
– Meerdere omgevingen goed kennen
– Geen integratie / “Cowboy-code”
Selection (Comparision of 13 Products)
– Product A: Perfect for GIS… only for GIS
– Product B: … not useable for GIS
– Product C: … not useable for CAD
– Product D: … not useable for Office
– Product E: … more cryptical than scripts
– Product F: … no support
– Product G: … since 2013 no new releases
FME
– The Only Perfect Match!
ETL Selection
FME !

16. Datasets:
– CAD / GIS / Raster / Data / Services
Applications:
– 18 Suppliers / 46 Applications / > 2500 Datasets
Integration:
– From “Hairball-Interfaces” to “Data-Integration-Plan”:
– Clear, manageable, documented, expandable interfaces.
Data - Quality:
– Corrections, integrity, quality control
Data - Enhancements:
– Combined, enhanced, scheduled data-sets
Data - Distribution:
– Data in the right form on the right place (distributed / push / pull)
– Business Intelligence / Context Intelligence / Location Intelligence
FME - Modellen:
– Even non-IT-personnel is able to model in FME
– Model = documentation
– Automatic en Manual workflows
FME in Lier

17. FME: The right data in the right form on the right place!

18. Conclusion: FME rocks!

19. Thank You!
Luc Janssens
• Data-, -Analysis- & GIS-coördinator
• Department Managementconsulting & Projectmanagement
• City of Lier, Belgium
luc.janssens@lier.be