Chapter 9: End-of-Chapter Questions

I. A data field consists of a single piece of data, or data element, such as employee number. Multiple, related fields are combined to form a record, such as an employee record. All like records are grouped to form a file, such as an employee file. All of the computer-based files of an organization can be regarded as the database.

2. Varina and Jones both have the Brutus book.

3. A flat file is important in developing a database because the requirement of non-repeating columns provides a format that lends itself to computer processing. The order of the fields is constant.

4. Data independence means that the description of the data (the data structure) is kept separate from the processes that use the data (the computer program). Data inconsistency comes about when the same logical data (such as a person’s address) is maintained in multiple data storage locations and the values are not the same. Redundant data is the same data that is repeated in more than a single location.

5. Structured query language is important because it is a standardized way to retrieve data or information from a database, usable on a wide variety of computer platforms.

6. The process-oriented approach to determination of data needs begins with an identification of the processes to be performed or the problems to be solved. The enterprise modeling approach begins with an identification of all of the data used by an enterprise.

7. The database administrator is responsible for database planning, implementation, operation, and security.

8. In terms of benefits, a DBMS can be expected to reduce data redundancy, achieve data independence, integrate data from multiple files, retrieve data and information rapidly, and improve security. The costs are those incurred to obtain expensive software, obtain a large hardware configuration, and hire and maintain a DBA staff.

9. Data warehouses and data marts are both gigantic storehouses of data. They differ in that the data mart is a subset of the data warehouse.

10. Using verification-driven data mining of your school’s student database as an example, the students will begin with their perception of how the data is related. This should be an interesting exercise in learning how students perceive what data about themselves is being maintained.

11. Data cleaning is the removal of errors in data. It is important to KDD because the use of artificial intelligence or statistical techniques assumes the availability of an accurate data warehouse.

12. In a hierarchical database structure, related records are identified in an explicit way, using link fields. In a relational database, records are related in an implicit way, using common data fields.

13. IBM’s efforts to gain standardization for SQL has enabled users to use databases without being constrained by the wide variety of hardware and software that are available, Once you learn to use SQL, you can use it on any computer hardware and software platform. Since large computers are required to manage large databases, where a query language is necessary, IBM benefited by selling larger numbers of large systems.

14. Implicit relationships use common fields to join data tables together. For example, in question

2 above, the common field in the two tables is the textbook title, and when the values in the common fields match, the rest of the fields in the record are also matched between the tables.

Topics for Discussion

2. An organization’s structure becomes flatter, managers must increase their productivity, performing tasks that were previously performed on multiple levels. As productivity demands increase, managers must interact personally with data. Managers are more likely to require data from outside their own functional area and this is empowered by constructing an interconnecting database.

3. Users can find unrecognized relationships among data by trying all possible combinations. This would be too time consuming on all but the smaller databases. The speed of the computer enables it to be used for verification-driven data mining.

4. Data collectors include data entry operators who enter data into databases. Data structures and maintainers are the database administrators. Data users are managers and other problem solvers. These are the three main groups of people who are involved with database creation and use. As hardware and software costs decline, people costs increase, making them the most important ingredient.