Analytics Training Curriculum

Analytics Training

 

Introductory training would cover data cube and analytics concepts and provide a high-level exposure to examining data in a pre-defined data cube using ProClarity.

 

Advanced training would teach how to install and configure iMIS Analytics, how to extract data from the data warehouse, how to use the Briefing Book, ad hoc queries, and how to put user defined data into data cubes (iMIS Customizer).

Analytics Concepts

  • Why not use real time data?
  • What is a data warehouse and how does it differ from a data cube?
  • What are the limitationsof a data warehouse?
  • What describes Data Cube structure?
  • How is the data extracted from the data warehouse?
  • What is an OLAP viewer?
  • What is multi-dimensional browsing?

Analytics Administrative Issues

  • What is Analytics comprised of, and what is it’s architecture?
  •  

    How can I configure Analytics for my existing servers?

  • What is ProClarity and what does it do?

iMIS Data Mining

  • What iMIS data is in the pre-defined data cubes?  iMIS Analytics Briefing Book
  • How is what I get from the existing iMIS reporting affected by Analytics?
  • How do I use Ad Hoc analysis?
  • How do you export the customer data to the ProClarity product?
  • How can I use iMIS Analytics to perform customer segmentation?
  • How do you include customer data (demographic data), aside from what is included in the pre-defined data cubes? – iMIS Customizer
  • How can I use my user defined data?
  • Can I use historical data from Backups? (This will be discouraged, so we may not want to address it in training.)

Concerns about the training

  • Where do we draw the line with teaching how to use ProClarity?
  • The clients are wanting to use the data cube utility directly. We don’t support that. Actually, using iMIS Customizer is not considered part of the support agreement.

I looked over the blog on Analytics in iMIS Communities. I am suggesting these Analytics issues to be addressed in training:

  • Tips on Revenue data - Brent S. and Eric Means
  • Set up of ETL.FiscalYearBegins - Mary Kay B.
  • Understanding measures in DWGroupStatsFact - Beth B. and Brent S.
  • Including UD fields in measures in Analytics - Mary Kay B.

 

Please let me know if you think these topics are appropiate. I can take out or add anything at this point.

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Re-working implementation estimates might help w/syllabus

Hi Monique,

I've been working away on the "Implementing Analytics" presentation for Innovations. Part of it is re-visiting the initial implementation estimates for Analytics. After talking to the implementators, I've come up with the following 2 phased approach for implementing Analytics. Perhaps this could be used to generate a syllabus:

Phase 1A
Educate/Confirm Dev Envr 1 - 4 hours
Installation 1 - 2 hours
Initial load of data into warehouse 1 - 4 hours
Inclusion of UD Data as attributes in customer dimensions 1 - 2 hours

Phase 1B
Creation of new cubes
- Enable demographic data as drill-down

24 - 40 hours
Additional BBK configuration 24 - 40 hours