This article looks at sets from an informational processing perspective; what they are; how they are constructed; and, distinct ways in which data can be drawn from sets within IRI software products using the SortCL data definition and processing program; i.e.,
There are a variety of testing requirements for any data warehouse and database — and especially dual platforms like Teradata — where ETL and BI prototypes, application stress testing, and performance benchmarking are essential.
The value of good test data to DBAs is well known:
“Testing of database-intensive applications has unique challenges that stem from hidden dependencies, subtle differences in data semantics, target database schemes, and implicit business rules.
This article is the last of a 4-step series introduced here.
Step 4: Test Data Sharing & Persistence
Being able to modify, deploy, store, and re-use test data is important.
This article is part of a 4-step series introduced here. Navigation between articles is below.Step 3: Test Data Generation & Provisioning
In prior steps outlined in this series, you have determined the purpose and properties of the data, and who will produce and consume it.
This article is part of a 4-step series introduced here. Navigation between articles is below.
Step 2: Test Data Needs Assessment
Once the questions of who needs test data for what — and who will be dealing with it along its lifecycle are answered (see Step 1) — a deeper dive is needed into the specific technical aspects of the data itself.
This article is part of a 4-step series introduced here. Navigation between articles is below.Step 1: Goal Setting & Team Building
Someone needs test data to do something, like:stress-testing the functions and performance of applications prototyping database load/query and DW ETL/ELT operations benchmarking prospective new hardware or software outsourcing development or proofs of concept demonstrating systems with real-looking, but not real, sample data
In all these cases, the most realistic data possible is needed, but it should also be safe and de-personalized.
Database and solution architects depend on realistic test data to:help create new databases, prototype ETL jobs or applications benchmark performance in new or existing platforms stress-test systems protect confidential information in existing systems if database work is outsourced or used for demonstrations.