Abstract: This article demonstrates how to synthesize realistic data to populate a full database schema with referential integrity in one operation via the IRI RowGen New Set File and New Database Test Data Job wizards in IRI Workbench. Read More
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., Read More
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. Read More
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. Read More
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. Read More
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. Read More
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. Read More
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. Read More