Methodologies provide a best practice framework for delivering successful business intelligence and data warehouse projects.
Depending on your requirements, we will draw on one or more of the following established methodologies.
Kimball data warehouse methodology
The Kimball Data Warehouse Methodology was developed by Ralph Kimball, who is widely regarded as the father of the data warehouse. Guidelines that every Kimball data warehouse should follow include:
- The primary objectives of a data warehouse should be performance and ease of use.
- Dimensional models can only be developed once information requirements have been understood and agreed.
- While the data warehouse will constantly evolve, each iteration should be considered a project life cycle consisting of predictable activities with a finite start and end.
Theta ETL infrastructure methodology
Theta’s ETL infrastructure methodology draws on experience implementing many data warehouse solutions using both WhereScape RED & Microsoft SQL Server Integration Services (SSIS). The ETL infrastructure is a set of processes, procedures and code that can be reused in a customer environment.
This infrastructure deals with:
- consistent method and content for entering operational metadata for loading data into the data warehouse environment;
- consistent methods for ETL error handling;
- consistent methods for ETL notifications;
The advantages of implementing the Theta ETL infrastructure methodology include;
- faster delivery (no re-inventing the wheel);
- consistency and simplicity for maintenance;
- minimise bugs and rework;
- leveraging of best practice and experience.
Theta’s Pragmatic Agile methodology
Theta uses an iterative approach to deploy data warehouse and BI solutions, where we prioritise components or features of the solution for deployment based on a combination of:
- high business impact (value);
- low cost (including risk);
- explicitly stated priorities of the business;
- dependencies between components.
The objective is to get as much value (usually in the form of information assets) into the hands of users, where it can provide the most value as quickly as possible.
This goes hand in hand with our iterative approach to BI development. Key elements include:
- Getting information to the users as quickly as possible, so they can see data and request relevant changes while development is under way.
- Developing and testing reports and dashboards in close collaboration with users.
The advantages of deploying solutions in a pragmatic, agile and iterative way include:
- early and visible return on investment;
- quick delivery to stakeholders and users;
- user requirements can be reviewed and revisited regularly;
- better control of the project from a delivery perspective;
- better financial control of the project.
See also: Data quality