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Online Analisys Processing

The use of OLAP is an approach allowing complex analytical multi-dimensional queries with rapid execution times. It is an integral component of data warehouses typically used for reporting for sales, marketing, management, budgeting and forecasting, finance and so on.

A key feature of Business Intelligence systems is their ability to provide historical and predictive views of business operations, usually using data gathered into a data warehouse (or a data mart). It is a common method to update data regularly, e.g. every day (typically saving data when the system is under less stress, e.g. during the night) or every given time so that each and every change in the data can be tracked and eventually used for analysis purposes.

It is thus clear that this approach contrasts with that of operational systems which perform day-to-day transaction processing.

In the picture below an analysis of the aggregate number of tickets for all cities, severities and categories

 

 

 

and can be exploded as to see how the number of tickets are distributed for every city,

 

 

 

as well as a more detailed description of the number of tickets of each category (e.g. EspSw:Backup, Reparacion, Suministros) with a severity of error in the city of San Mateo.

 



 

All the views shown above can be obtained virtually instantly, as all calculations do not need to be processed but are already in the system and can be easily saved.

For the vtiger CRM - BI project we have created cubes to study:

  • Sales Cube (Invoice and Invoice lines)
  • Support Cube (Helpdesk)
  • Marketing Cube (Campaign/Invoice)
  • Commercial Cube (Opportunities/Invoice)
  • Price Cube (PriceBook)

Indirectly we can study the entities:

  • Users
  • Products
  • Accounts
  • Contacts

These cubes will permit you to navigate through your invoice lines in search of most sold products, client buying trends, best selling time frames for your products and/or clients, products or clients with high/low support needs, products with excessive support requests, sales departments opportunity conversion rates and many other questions that arise while working with the cubes. It is a new way of looking at your company, it is stimulating, permitting your imagination ask questions and structure the cube to receive the answers.

 

This takes us to one of the most important parts of the BI project: Reporting and Dashboards.


  • This is the first OLAP cube of the payments cube
  • These are the dimensions we can navigate and study on
  • In the next screen I have changed the initial cube to contact city by year
  • This is how that last configuration looks
  • This is the same cube but with yearly payment opened up. Anybody who has played with OLAP before knows how easy and stimulating navigating through your data is!!
  • The same cube with cities opened up
  • This can just as easily be taken to quartely payments by years with a graph. Impressive!!
  • Some of the dimensions and measures that can be used while studying invoices
  • Some of the dimensions and measures that can be used while studying invoices
  • Here we can see HelpDesk measures that can be used
  • a state of the Potentials cube