Thursday, April 6, 2017
09:30 AM - 10:15 AM
A modern data architecture manages data in many different forms:
- Normalized data
- Non-relational data
- Semi-structured data available from diverse sources and a range of formats
- Data Vault data
- Dimensional data in information marts for reporting/business intelligence
The variety of forms and volume of data means that data transformation is a complex and costly aspect of any modern data environment.
Previously we have shown that Fact-Based Modeling can be used as a unified modeling approach managing conceptual data semantics across all these different forms. In this talk we will focus on showing that a Fact-Based Modeling conceptual query language can be used to automatically generate transformation code from source, through a data warehouse and to information marts.
We will apply this approach in two distinct environments:
- A traditional data warehouse based on Data Vault
- A cloud-based data warehouse
We'll show that automated transformation code generation from a conceptual query language reduces cost, contains fewer errors, and supports change/agility.
Dr. Graeme Port has been an innovator and leader in enterprise software product development and data architecture for over 30 years. Graeme was co-founder, head of engineering and CTO at ManageSoft, which built market-leading products in application development, application deployment and business intelligence. Graeme received his PhD from the University of Melbourne in the field of Logic Programming.