This document discusses how to transform raw data into useful business intelligence using FME. It explains that FME makes it easy to connect to various data sources, clean the data, and generate visualizations and reports. Examples of visualizations include geospatial dashboards in QlikMaps and Tableau for analyzing sales performance and infrastructure asset management. The document promotes FME's ability to prepare data for business intelligence applications to help organizations make informed decisions.
5. Step 1: Connect to the data
Transformers
● HTTPCaller*
● HTMLExtractor
● S3 Transformers
● DropboxConnector
● OneDriveConnector
● BoxConnector
● GoogleDriveConnector
● AutodeskA360Connector
● DatabaseJoiner
Database Formats
● Oracle
● MS SQL Server
● PostgreSQL
● IBM Cloudant
● Teradata
● PostGIS
● SQLite
● Netezza
Web Formats
● ArcGISOnline
● Salesforce
● Socrata
● Google Sheets
● MongoDB
● Amazon DynamoDB
● HTML Table Reader
● IBM dashDB
6. ● Amazon Web Services
● OAuth 2.0 (10,000’s of web
services)
● Good old Token based
● HTTP Authentication
(Basic, Digest, NTLM)
Web Connections
Connection Support is extensive!
Step 1: Connect to the data
7. Step 2: Clean it up
Keep the good. Filter out the bad. Clean up the ugly.
17. Leaders in
Visualization
ü QlikMaps (new in FME 2017)
ü Tableau
ü Microsoft Power BI and
others: Write to a
format supported by
that application
Source: Gartner
20. QlikMaps
● By Analytics8, a big data & analytics consulting firm
specializing in business intelligence.
○ Qlik: business intelligence.
○ QlikMaps: geospatial business intelligence.
● Adds the value of location, spatial features, web map
services, and search functionality to Qlik.
21. 3 Common QlikMaps Use Cases
● Visualizing and managing sales performance.
● SLA (service level agreements) compliance.
● Movement of goods, services, and people.
22. Challenge: Passenger Flow at
the Airport
● Track and improve passenger flow.
● Increase passenger satisfaction.
● Gain insight into commercial opportunities for
retailers.
25. Challenge: Visualizing Sales KPIs
● Visualize by product group + by geographies.
● Look for regional trends.
● Cluster by distance.
● Present location analytics for meaningful insights.