I know several small companies do not do testing on ETL process, but that seems to be suboptimal from the perspective of software engineering. How do people usually do testing/unit test/functional.
Deepa, Estimation template is not the same for all the projects. So there is nothing like specific template for estimation.
All that you need to take care is you have to make sure how many resources are there and how many mappings are there(depends on complexity) to develop and need to estimate the time line. This estimation should include testing of the mapping also. As a developer by seeing the requirement we know how many days it will take, so we can keep some buffer time in estimation. -Bala -----Original Message----- hey wt do u mean by estimation template. I would suggest you to Look into Ralph Kimball's Data warehousing tool kit.
First few chapters initiates with the prepartion of BRT( Business Requirement Templates), and effort estimation and all other stuffs required when you intially start off with your project. I belive that would provide you with some good inputs. Best of Luck. Cheers Arun On Fri, Sep 5, 2008 at 11:10 AM, mkishorekumar via informatica-l wrote: > > > > > hey wt do u mean by estimation template > > On 9/4/08, dsivan via informatica-l > wrote: > > > > > > > > > > > > Hi Folks, > > > > Can anyone please post a sample estimation effort template(ETL). > > > > Thanks, > > > > Deepa. These are the books from the author Ralph Kimball.worth reading and understanding core concepts related to dimensional modelling, ETL and datawarehouse loads, dependencies, challenges many more.its available in stores.wiley publications. /Rajiv -----Original Message----- Hi, Pls.
Suggest, where from can I get Datawarehouse Tool Kit and Datawarehouse ETL tool kit? Sorry if this sounds to be dumb quetion. I am working with my own testing environment, hence would be benefitted, if you can provide the same. Regards, ~Harish.
You probably use checklists to record and efficiently execute a wide range of daily work tasks. But if you don’t use checklists for developing and monitoring your data warehouse quality assurance (QA), you’re missing an enormous boost in productivity and proficiency.
Procedural data warehouse checklists serve as concrete reminders of which jobs we need to perform and the order in which we need to perform them. They are an informational aid used to reduce failure by compensating for the potential limits of human memory and attention. In this article, I will provide test planners and testers with ideas for data warehouse checklists that help them avoid often-overlooked tasks, including tasks that require special attention during the complexity of data warehouse test planning and test execution efforts.
Checklists can help with the development of the overall test strategy, the selection and prioritization of test cases, and the successful completion of troubleshooting. Unit testing checklist Some programmers are not well trained as testers. They may like to program, deploy the code, and move on to the next development task without a thorough unit test. A checklist will aid database programmers to systematically test their code before formal QA testing.
• Check the mapping of fields that support data staging and in data marts. • Check for duplication of values generated using sequence generators.
• Check the correctness of surrogate keys that uniquely identify rows of data. • Check for data-type constraints of the fields present in staging and core levels. • Check the data loading status and error messages after ETLs (extracts, transformations, loads). • Look for string columns that are incorrectly left or right trimmed. • Make sure all tables and specified fields were loaded from source to staging. • Verify that not-null fields were populated.
• Verify that no data truncation occurred in each field. • Make sure data types and formats are as specified during database design. • Make sure there are no duplicate records in target tables. • Make sure data transformations are correctly based on business rules.
• Verify that numeric fields are populated precisely. • Make sure every ETL session completed with only planned exceptions. • Verify all data cleansing, transformation, and error and exception handling. • Verify stored procedure calculations and data mappings. Integration testing checklist An integration test checklist helps ensure that ETL workflows are executed as scheduled with correct dependencies. • Look for the successful execution of data-loading workflows. • Make sure target tables are correctly populated with all expected records, and none were rejected.
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