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Chapter 12 File Processing and Data Management Concepts

Chapter 12 File Processing and Data Management Concepts. Presentation Outline. Terminology Database Technology The Architecture of a Database Management System (DBMS) The Database Administrator. I. Terminology. Field Data Occurrences Fixed vs. Variable Length Records Record Key

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Chapter 12 File Processing and Data Management Concepts

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  1. Chapter 12File Processing and Data Management Concepts

  2. Presentation Outline • Terminology • Database Technology • The Architecture of a Database Management System (DBMS) • The Database Administrator

  3. I. Terminology • Field • Data Occurrences • Fixed vs. Variable Length Records • Record Key • Sort Keys

  4. A. Field A field is the smallest block of data that will be stored and retrieved in the information system. Other names for field include data item, attribute, or element. Field 1 Field 2

  5. B. Data Occurrences A specific set of data values for a record in a file. 1 2 3 4 5 The above table contains 5 occurrences of account records for the general ledger account file.

  6. Fixed Length Records Both the number of fields and the length of each field are fixed. Strength: Easier to manipulate records. Weakness: Must accommodate maximum sizes. Variable Length Records Both the number of fields and the length of each field are variable. (See Fig. 15-1 on p. 603) Strength: Less waste of memory when maximum sizes do not have to be accomodated. Weakness: Record manipulation is more difficult. C. Fixed vs. Variable Length Records

  7. D. Record Key 1110 A record key is a field or combination of fields that uniquely identifies a particular record in a file. 1500 2105 2110

  8. E. Sort Keys • Primary sort key – The first field used to sort the data occurrences in a record set. • Secondary sort key – A field used to determine relative position among a set of data occurrences in a record set. • Tertiary sort key – Additional fields beyond primary and secondary sort keys that are required to uniquely identify data occurrences in a record set.

  9. II. Database Technology • The Problem of Redundancy • The Components of a Database

  10. A. The Problem of Redundancy That is not what we show per our records. • Redundancy occurs when different areas of an organization use the information system to store the same information in more than one place. • Results in update anomaly.

  11. B. The Components of a Database Management System • Data Description Language (DDL) • Data Manipulation Language (DML) • Data Query Language (DQL)

  12. 1. Data Description Language (DDL) Defines the logical structure of the database (known as the schema). Defines the following: • Name of data fields. • Type of data (numeric, alphabetic, etc.) • Number of positions (length of field). • May also define subschema (i.e., individual user views)

  13. 2. Data Manipulation Language (DML) Pull a trial balance. • The DML consists of the commands for updating, editing, manipulating, and extracting data. • Structured query language (SQL) is a common DML in relational settings. Structure Query Language (SQL)

  14. 3. Data Query Language Query by Example (QBE) A data query language is a user friendly language or interface that allows the user to request information by simply filling in blanks. Represents a special type of DML.

  15. III. The Architecture of a Database Management System (DBMS) • The Database Architecture • The Conceptual Architecture and Entity-Relationship (ER) Diagrams • Logical Data Structures • The Physical Structure

  16. A. The Database Architecture Database contents Uses of database Desired reports Information to be viewed Conceptual Level Logical data structures: Tree Network Relational Logical Level Access Methods: Sequential Access Indexed Files Physical Level

  17. B. The Conceptual Architecture and Entity-Relationship (ER) Diagrams PART_NO NAME • Square boxes are used for entities (separate tables). • Ellipses are used for attributes (table columns). • Diamond shaped boxes depict relationships. COST PART STORED AT LOCATION WHSE ADDRESS

  18. C. Logical Data Structures • Tree or Hierarchical Structure • Network Structures • Relational Structure • Selection • Projection • Join

  19. 1. Tree or Hierarchical Structure • A parent record can have many children. However a child record can have only one parent. • Can only model 1:1 (one-to-one) and 1:* (one-to-many) relationships. • Commonly used with accounting data. Can only access data by going from a parent to child. Balance Sheet Assets Liabilities Equity Current Assets Current Liabilities Revenues Long-term Assets Long-term Liabilities Expenses

  20. 2. Network Structure • Eliminates the distinction of parent and child records. A parent can have many children and a child can have many parents. • Can model 1:1 (one-to-one), 1:* (one-to-many), and *:* (many-to-many) relationships. • Must know the physical structure of the data in order to access it.

  21. 3. Relational Structure • Relational databases organize and store data in two dimensional tables consisting of rows and columns. • Relationships among tables are represented by common data values in different tables. • Straight forward in terms of organizing and searching the data. • Possesses ad hoc search capabilities.

  22. 3a. Selection Savings Table Produces a horizontal subset (includes entire row) of a relation which satisfies a boolean predicate. (Savings) Balance < 5.00

  23. 3b. Projection Savings Table Constructs a vertical subset of a relation. The subset is obtained by selecting specified attributes and removing others. (Savings) Name Balance < 5.00

  24. 3c. Join Table R Table S A join is used to combine 2 tables. The attribute used to join must be in both tables. R |X| S

  25. D. The Physical Structure • Sequential Access • Indexed Files

  26. 1. Sequential Access • Records can only be accessed in a predefined sequence. For example, if there are 100 records in a file, one must access the first 99 records before accessing the last record. • Generally useful for batch processing when nearly all records must be accessed.

  27. 2. Indexed Files • Any attribute can be extracted from the records in a primary file and used to build a new file whose purpose is to provide an index to the original file. • First, the index is searched to find a specified value of an attribute such as an customer account number. • Second, the disk addresses are used to directly retrieve the desired records • See Fig. 12-13 on p. 427.

  28. IV. The Database Administrator This is not quite what we need. The database administrator is a person who coordinates data management activities such as approving the physical contents and user views of the database.

  29. Summary • Fields and keys • Three Components of a DBMS • Three Types of Database Architecture • The Database Administrator

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