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Semantics
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If you want to use information systems correctly, you must be aware of the semantics (the meaning of things) of the underlying data model. A careful choice for table names and column names is a good starting point, followed by applying those names as consistently as possible. For example, the attribute address can have many different meanings: home address, work address, mailing address, and so on. The meaning of attributes that might lead to this type of confusion can be stored explicitly in an additional semantic explanation to the data model. Although such a semantic explanation is not part of the formal data model itself, you can store it in a data dictionary a term explained in the next section.
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Information Systems Terms Review
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In this section, the following terms were introduced: Entities and attributes Generic versus specific Occurrences and attribute values Base data and derivable data Redundancy and consistency Integrity and constraints Data modeling Methods and techniques Logical and physical design Normalization Prototyping and RAD CASE tools Semantics
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1.3 Database Management Systems
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The preceding two sections defined the formal concept of an information system. You learned that if an organization decides to automate an information system, it typically uses some database technology. The term database can be defined as follows:
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Definition A database is a set of data, needed to derive the desired information from an information system and maintained by a separate software program.
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This separate software program is called the database management system (DBMS). There are many types of database management systems available, varying in terms of the following characteristics: Price Ability to implement complex information systems Supported hardware environment Flexibility for application developers Flexibility for end users Ability to set up connections with other programs Speed Ongoing operational costs User-friendliness
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DBMS Components
A DBMS has many components, including a kernel, data dictionary, query language, and tools.
Kernel
The core of any DBMS consists of the code that handles physical data storage, data transport (input and output) between external and internal memory, integrity checking, and so on. This crucial part of the DBMS is commonly referred to as the engine or kernel.
Data Dictionary
Another important task of the DBMS is the maintenance of a data dictionary, containing all data about the data (the metadata). Here are some examples of information maintained in a data dictionary: Overview of all entities and attributes in the database Constraints (integrity) Access rights to the data Additional semantic explanations Database user authorization data
Query Languages
Each DBMS vendor supports one or more languages to allow access to the data stored in the database. These languages are commonly referred to as query languages, although this term is rather confusing. SQL, the language this book is all about, has been the de facto market standard for many years.
RELATIONAL DATABASE SYSTEMS AND ORACLE
Other Query Languages, Really
SQL is such a common query language that very few realize that there were ever any others. In fact, few even comprehend the concept that there can be other languages than SQL. But there are others. Oracle Rdb supports SQL, but Rdb also supports a language called Relational Database Operator (RDO). (Yes, you ve heard it here: there was an RDO long before Microsoft took up that abbreviation). RDO is a language developed by Digital Equipment Corporation (DEC) for use in their own database management system. Oracle bought that system, and continues to support the use of RDO to this day.The Ingres database, once a competitor to Oracle, also had its own query language. Ingres originally supported a language known as Quel. That language did not compete well with SQL, and Ingres Corporation was eventually forced to build SQL support into their product.Today, SQL is the dominant database access language. All mainstream relational databases claim to support it. And yet, no two databases support it in quite the same way. Instead of completely different languages with dissimilar names, today we have variations that we refer to as Oracle SQL, Microsoft SQL, DB2 SQL, and so forth. The world really hasn t changed much.
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