Data programs are classified into two big categories, according to intercontinental developments: A. On-line transactional processing programs (also known as operational programs)
B. Determination help programs (DSS)
Α. On-line transactional processing programs OLTPs are programs which serve transactions with suppliers, associates and buyers, as well as internal business enterprise transactions. They help operations through the value chain of the Firm:
- Provide Chain Management (SCM)
- Manufacturing help (e.g. MRP, State-of-the-art Scheduling & Scheduling)
- Buyer interface administration (e.g. profits, buy administration and billing) (CRM)
- Finance and Accounting (ERP)
- Income pressure automation
- Net channel operations (eCRM)
- Internal workflow help programs
Β. Determination help programs DSS supply administration at all levels of the Organisation, with data which supports comprehending of the recent Business enterprise posture and getting knowledgeable choices (actuality dependent administration). OLTP vs DSS programs Even while OLTP (on-line transactional processing) and DSS (choice help programs) functionalities may perhaps overlap (e.g. an OLTP process may perhaps supply some operational reporting functionality utilised for choice help), it is distinct that the purpose of the two categories differs, presented that they serve different functions and different Person groups in the Business enterprise. Consequently the advancement philosophy of the two categories differs radically. Precisely, variations are identified on the adhering to conditions (1 for OLTP, two for DSS): Method practical demands:
- Obviously specified presented that the process serves specific practical requires – the predetermined transactions
- the dedication of a comprehensive prerequisite set is a challenge, presented that there are dynamically modifying informational demands.
Capture of recent and historical data:
- Existing point out data is captured (some historical data may perhaps exist only to serve opportunity long run transactions)
- New and historical data is captured (recent may perhaps not be captured, presented that data from the OLTP are retrieved at standard intervals)
Information products utilised:
- Elaborate, centered on business enterprise entities (in terms of relational databases it is known as normalized data framework (e.g. 3NF))
- Unique strategies exist. The simplified denormalised dimensional framework gains momentum, given that it enables much easier comprehending by business enterprise buyers and optimized execution of elaborate queries.
Data amount of depth:
- Comprehensive data for each transaction are held
- Comprehensive data are held in a different framework and are enriched by ‘dimensional’ data which enables analytical processing. Also, aggregated data like KPIs (important general performance indicators), are calculated and saved in persistent storage.
Quantity of data:
- The quantity of data is related to the size of the Business enterprise and the penetration of IT in it.
- The data quantity managed by a DSS, is various of that of the OLTP programs on which it is dependent, presented that it maintains various historical snapshots
Copyright 2006 – Kostis Panayotakis