Watch — analysing your business data
| Learning channels: |  Private web class |
On-site training |
Do you want to analyse your own performance over SWIFT or do you want to access key data about SWIFT across markets and countries? How many messages are you sending and receiving per month? Which message types? How is your traffic volume evolving? What is your market share of your country’s total SWIFT traffic? Who are your main counterparties? What is the average price of your messages? What is your total cost of ownership of SWIFT?
This comprehensive course gives you direct and easy access to business intelligence about your own institution as well as the overall market through either a private web class or hands-on training on your premises.
This course is given on special request only, please contact your regional SWIFT office for more information Download this course description in PDF
Audience
This course is targeted at staff responsible for analysing the SWIFT business data of their company and who are registered Watch end users. (If another person would like to attend as well, he should first register as new end user or provide a justification.)
You will learn
- About the different Watch Analysers that are part of the Watch portfolio
- About the basic functionalities of the Watch Analysers
- How to compose and interpret your own analyses
- How to use the Analysers by completing yourself a number of practical case scenarios on Watch
Course content
- Watch portfolio overview
- Watch Analysers - dimensions and measures
- How to build results tables (drag & drop, filters, drilling down, expanding, nesting, etc.)
- How to work with data (sorting, hiding, ranking, subsets, charts, etc.)
- Extra (exporting, bookmarking, reports, etc.)
- Practical case scenarios on all your Watch Analysers
Prior knowledge
It is recommended to have prior knowledge about your business with SWIFT.
Duration
The course duration depends on the learning channel you choose:
- On-site training: up to 1 day as per your requirements
- Private web class: 3,5 hours