Answer Posted / sonia kapoor
Information systems are classified into two major
categories, according to international developments: A. On-
line transactional processing systems (also called
operational systems)
B. Decision support systems (DSS)
Α. On-line transactional processing systems OLTPs are
systems which serve transactions with suppliers, partners
and customers, as well as internal business transactions.
They support operations throughout the value chain of the
Organization:
Supply Chain Management (SCM)
Production support (e.g. MRP, Advanced Planning &
Scheduling)
Customer interface management (e.g. sales, order management
and billing) (CRM)
Finance and Accounting (ERP)
Sales force automation
Web channel operations (eCRM)
Internal workflow support systems
Β. Decision support systems DSS provide management at all
levels of the Organisation, with information which supports
understanding of the current Business position and taking
informed decisions (fact based management). OLTP vs DSS
systems Even though OLTP (on-line transactional processing)
and DSS (decision support systems) functionalities may
overlap (e.g. an OLTP system may provide some operational
reporting functionality used for decision support), it is
clear that the purpose of the 2 categories differs, given
that they serve different functions and different User
groups in the Business. Therefore the development
philosophy of the two categories differs radically.
Specifically, differences are identified on the following
criteria (1 for OLTP, 2 for DSS): System functional
requirements:
Clearly specified given that the system serves specific
functional needs – the predetermined transactions
the determination of a complete requirement set is a
challenge, given that there are dynamically changing
informational requirements.
Capture of current and historical information:
Current state information is captured (some historical data
may exist only to serve potential future transactions)
Recent and historical information is captured (current may
not be captured, given that data from the OLTP are
retrieved at regular intervals)
Data models used:
Complex, focused on business entities (in terms of
relational databases it is called normalized data structure
(e.g. 3NF))
Different approaches exist. The simplified denormalised
dimensional structure gains momentum, since it allows
easier understanding by business users and optimized
execution of complex queries.
Information level of detail:
Detailed data per transaction are kept
Detailed data are kept in a different structure and are
enriched by ‘dimensional’ information which allows
analytical processing. Moreover, aggregated data like KPIs
(key performance indicators), are calculated and stored in
persistent storage.
Volume of data:
The volume of data is relevant to the size of the Business
and the penetration of IT in it.
The data volume handled by a DSS, is multiple of that of
the OLTP systems on which it is based, given that it
maintains multiple historical snapshots
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