This document gives an overview of the PhixFlow training courses. You can use this document to decide which courses are appropriate for each person in your company that will be using PhixFlow.
As a guide there are typically three roles to be covered by PhixFlow users:

End User
Designer
Administrator

End users will usually receive training specifically for the applications in PhixFlow that they will use. These training materials are developed as part of implementation projects, and may be created and delivered by PhixFlow, the organisation itself, or often by the organisation with support from PhixFlow - whatever is most suitable for each project, and each application.

Depending on the size and type of your organisation, groups of users may be required to carry out all roles or only a subset of roles e.g. a medium or large organisation will have a dedicated administrator, whereas in a smaller organisation a user may need to be familiar with all roles.
The table below gives a recommended set of courses for each role:

		Role
		Designer	Administrator
Course	Introduction to Modelling	1 day	1 day
	Modelling Concepts	2 day
	Advanced Modelling	1 day

Course Descriptions

All PhixFlow courses are hands-on and include a mixture of PowerPoint presentation and exercises. Courses are held either at our offices in Cambridge, UK, or at your own offices. When courses are held at a customer site, all that is required is a dedicated room with a projector screen, and a PC per candidate with access to the internet – no software needs to be installed.

PhixFlow Introduction to Modelling (1 day)

Aims:
After attending this course the user will be able to create and operate simple models in PhixFlow. The user will be able to create and use all the principal components of PhixFlow modelling: file and database collectors, streams, file and database exporters; alarm generators.
Prerequisites:
Attendees should have a basic knowledge of using computers and of the type of issues that PhixFlow will be addressing in your organisation. Experience of using Excel style formulas is helpful for PhixFlow modelling.
Note that this course includes a session on data collection which makes use of some basic SQL. Knowledge of SQL is not essential for users who do not intend to build their own database collectors after the course.
Course Content:

Creating and using File Collectors and Database Collectors.
Creating and using Streams.
Attribute Functions and basic scripting.
Creating and using File Exporters and Database Exporters.
Creating and using Alarm Generators.
Running Streams, rolling back data in models, setting up Task Plans.

PhixFlow Modelling Concepts (2 days)

Aims:
After attending this course the user will be able to build and operate models in PhixFlow to handle most commonly occurring problems. This course builds on the Introduction to Modelling course by exploring the fundamental concepts behind PhixFlow models, covers many advanced features of PhixFlow modelling, and works through many common use cases.
Prerequisites:
The candidate must have attended the Introduction to Modelling course.
Course Content:

Concepts behind PhixFlow models: Stream Sets; Candidate Sets; the Timing Cycle.
Common use cases: combining data sets; picking out records according to business rules; de-duplicating; exploding out record sets.
Data enrichment from external databases.
Loading and using reference data.
Copying modelling components, and models.
Copying/moving Stream data.
Exporting/importing modelling components, and models.
Advanced scripting and creating macros.
Trouble shooting.
Creating and using workflows.

PhixFlow Advanced Modelling (1 day)

Aims:
After attending this course the user will understand how to tune PhixFlow models to optimise performance when handling large volumes of data, and also some advanced features of file processing, fuzzy matching, and data collection from external databases.
Prerequisites:
The candidate must have attended the Modelling Concepts course.
Course Content:

Enriching small data sets from very large data sets.
Enriching large data sets from very large data sets.
Fuzzy matching.
Advanced file processing.
Advanced database collection.

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