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Design analysis [5] should establish the scalability of an ETL system across the lifetime of its usage – including understanding the volumes of data that must be processed within service level agreements. The time available to extract from source systems may change, which may mean the same amount of data may have to be processed in less time.
Data requirements can also be identified in the contract via special contract clauses (e.g., DFARS), which define special data provisions such as rights in data, warranty, etc. SOW guidance of MIL-HDBK-245D describes the desired relationship: "Work requirements should be specified in the SOW, and all data requirements for delivery, format, and ...
Migration addresses the possible obsolescence of the data carrier, but does not address that certain technologies that use the data may be abandoned altogether, leaving migration useless. Time-consuming – migration is a continual process, which must be repeated every time a medium reaches obsolescence, for all data objects stored on a certain ...
Level Test Design (LTD): Detailing test cases and the expected results as well as test pass criteria. Level Test Case (LTC): Specifying the test data for use in running the test cases identified in the Level Test Design. Level Test Procedure (LTPr): Detailing how to run each test, including any set-up preconditions and the steps that need to be ...
Note that in many cases the statement of work is a binding contract. [2] Master service agreements or consultant/training service agreements postpone certain work-specific contractual components that are addressed in individual statements of work. The master service agreement serves as a master contract governing the terms over potentially ...
A service-level agreement can track multiple performance metrics. In this context, these metrics are called service level indicators (SLIs). The target value of a given SLI is called a service-level objective (SLO). In IT-service management, a common case is a call center or service desk. SLAs in such cases usually refer to the following SLIs:
Testing evolves to merely validate that the test service operates according to its documentation, and finds gaps in documentation and test cases of all services within the environment. Managing the data state of idempotent services is the only complexity. Examples may prove useful to aid in documenting a service to the level where it becomes ...
Schema migration allows for fixing mistakes and adapting the data as requirements change. They are an essential part of software evolution, especially in agile environments (see below). Applying a schema migration to a production database is always a risk. Development and test databases tend to be smaller and cleaner.