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2004 Prentice Hall Business Publishing, Accounting Information Systems, 9/e, by Bodnar/Hopwood 12– 1 Chapter 12 File Processing and Data Management Concepts.

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Presentation on theme: "2004 Prentice Hall Business Publishing, Accounting Information Systems, 9/e, by Bodnar/Hopwood 12– 1 Chapter 12 File Processing and Data Management Concepts."— Presentation transcript:

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2 2004 Prentice Hall Business Publishing, Accounting Information Systems, 9/e, by Bodnar/Hopwood 12– 1 Chapter 12 File Processing and Data Management Concepts

3 2004 Prentice Hall Business Publishing, Accounting Information Systems, 9/e, by Bodnar/Hopwood 12 – 2 Learning Objective 1 Define the basic terms used in database technology.

4 2004 Prentice Hall Business Publishing, Accounting Information Systems, 9/e, by Bodnar/Hopwood 12 – 3 Introductory Terminology Field Data items Attribute Elements These are used interchangeably to denote the to denote the smallest block of data that will be stored and retrieved.

5 2004 Prentice Hall Business Publishing, Accounting Information Systems, 9/e, by Bodnar/Hopwood 12 – 4 Introductory Terminology A field may be a single character or number, or it may be composed of many characters or numbers. Customer name Employee social security number Purchase order number Customer account number

6 2004 Prentice Hall Business Publishing, Accounting Information Systems, 9/e, by Bodnar/Hopwood 12 – 5 Introductory Terminology Logical grouping of fields are called records. An employee A customer A vendor An invoice

7 2004 Prentice Hall Business Publishing, Accounting Information Systems, 9/e, by Bodnar/Hopwood 12 – 6 Data Occurrences A record occurrence is a specific set of data values for the record.

8 2004 Prentice Hall Business Publishing, Accounting Information Systems, 9/e, by Bodnar/Hopwood 12 – 7 Data Occurrences For the record EMPLOYEE (NAME, NUMBER, AGE) we might have the occurrence EMPLOYEE (Brown, , 33)

9 2004 Prentice Hall Business Publishing, Accounting Information Systems, 9/e, by Bodnar/Hopwood 12 – 8 Fixed- and Variable-Length Records In a fixed-length record, both the number of fields and the length (character size) of each field are fixed. In variable-length records, the width of the field can be adjusted to each data occurrence. A trailer record is an extension of a master record.

10 2004 Prentice Hall Business Publishing, Accounting Information Systems, 9/e, by Bodnar/Hopwood 12 – 9 Several Suppliers and Warehouses Example PART_NOPNAMETYPECOST PVEND – the name of the vendor or supplier WARHSE – where the part is stored LOC – the last two digits of the zip code

11 2004 Prentice Hall Business Publishing, Accounting Information Systems, 9/e, by Bodnar/Hopwood 12 – 10 One Storage Location Example PART (PART_NO, PNAME, TYPE, COST, PVEND #1, WARHSE #1, LOC#1, PVEND #2, WARHSE #2, LOC#2)

12 2004 Prentice Hall Business Publishing, Accounting Information Systems, 9/e, by Bodnar/Hopwood 12 – 11 Repeated Groups Repeated groups are related groups of fields that repeat themselves in variable-length records. SegmentsGroupsNodes PART, SUPPLIER, and LOCATION can be written as follows: PART (PART_NO, PNAME, TYPE, COST)

13 2004 Prentice Hall Business Publishing, Accounting Information Systems, 9/e, by Bodnar/Hopwood 12 – 12 Tree Diagram for PART, SUPPLIER and LOCATION PART SUPPLIERLOCATION

14 2004 Prentice Hall Business Publishing, Accounting Information Systems, 9/e, by Bodnar/Hopwood 12 – 13 Record Key and File Sequence A key or record key is a data item or combination of data items that uniquely identifies a particular record in a file. Primary sort key Secondary sort key Tertiary sort keys Relative random order

15 2004 Prentice Hall Business Publishing, Accounting Information Systems, 9/e, by Bodnar/Hopwood 12 – 14 Learning Objective 2 Identify the three levels of database architecture.

16 2004 Prentice Hall Business Publishing, Accounting Information Systems, 9/e, by Bodnar/Hopwood 12 – 15 Database Management Systems and Their Architecture Conceptuallevel Database contents Uses of database Desired reports Information to be reviewed

17 2004 Prentice Hall Business Publishing, Accounting Information Systems, 9/e, by Bodnar/Hopwood 12 – 16 Database Management Systems and Their Architecture Logicallevel Logical data structures: Tree (hierarchical) Tree (hierarchical) Network Network Relational Relational

18 2004 Prentice Hall Business Publishing, Accounting Information Systems, 9/e, by Bodnar/Hopwood 12 – 17 Database Management Systems and Their Architecture Physicallevel Access methods: Sequential Sequential Indexed-sequential Indexed-sequential Direct Direct

19 2004 Prentice Hall Business Publishing, Accounting Information Systems, 9/e, by Bodnar/Hopwood 12 – 18 Conceptual Architecture The Entity-Relationship (E-R) data model is a conceptual model for depicting the relationships between segments in a database. Attribute refers to individual fields or data items.

20 2004 Prentice Hall Business Publishing, Accounting Information Systems, 9/e, by Bodnar/Hopwood 12 – 19 Conceptual Architecture The object-oriented modeling technique (OMT) views the components of the system being modeled as object classes. Object class corresponds to a segment. Object corresponds to a particular instance.

21 2004 Prentice Hall Business Publishing, Accounting Information Systems, 9/e, by Bodnar/Hopwood 12 – 20 Example of Object-Oriented Data Modeling Technique PLANT_EQUIPMENTACCOUNT_NOCOSTDEPRECIATION HEAVY_EQUIPMENT HEAVY_EQUIPMENT MAINTENANCE_FREQ MAINTENANCE_FREQ DATE_PURCHASED DATE_PURCHASEDHAND_TOOLSUSAGE

22 2004 Prentice Hall Business Publishing, Accounting Information Systems, 9/e, by Bodnar/Hopwood 12 – 21 Learning Objective 3 Compare and contrast the different logical models of databases.

23 2004 Prentice Hall Business Publishing, Accounting Information Systems, 9/e, by Bodnar/Hopwood 12 – 22 Logical Data Structures The relationships that exist between the segments in the database are determined by the logical data structure, also called the schema or database model.

24 2004 Prentice Hall Business Publishing, Accounting Information Systems, 9/e, by Bodnar/Hopwood 12 – 23 Logical Data Structures What are the three major models of logical data structure? 1. Tree or hierarchical structures 2. Network structures 3. Relational models

25 2004 Prentice Hall Business Publishing, Accounting Information Systems, 9/e, by Bodnar/Hopwood 12 – 24 Logical Data Structures Tree (hierarchical) model (4 levels and 13 nodes) A BCDE FGHIJK LM

26 2004 Prentice Hall Business Publishing, Accounting Information Systems, 9/e, by Bodnar/Hopwood 12 – 25 Logical Data Structures ABC DFEGHI JK Network model (3 levels and 11 nodes)

27 2004 Prentice Hall Business Publishing, Accounting Information Systems, 9/e, by Bodnar/Hopwood 12 – 26 Logical Data Structures Both trees and networks are implemented with imbedded pointer fields.

28 2004 Prentice Hall Business Publishing, Accounting Information Systems, 9/e, by Bodnar/Hopwood 12 – 27 Implementing Tree and Network Structures In a list organization, each record contains one or more pointers (fields) indicating the address of the next logical record with the same attribute(s). A ring structure differs from a list in that the last record in the ring list points back to the first record.

29 2004 Prentice Hall Business Publishing, Accounting Information Systems, 9/e, by Bodnar/Hopwood 12 – 28 Implementing Tree and Network Structures What is a multiple ring structure? In this type of structure several rings pass through individual records.

30 2004 Prentice Hall Business Publishing, Accounting Information Systems, 9/e, by Bodnar/Hopwood 12 – 29 List Structure Records Red Blue Index Location of first record Attribute Pointer field to next record End of list indicator

31 2004 Prentice Hall Business Publishing, Accounting Information Systems, 9/e, by Bodnar/Hopwood 12 – 30 Ring Structure Records Va Ky Index Location of first record Attribute Pointer field to next record Pointer field to first record 2

32 2004 Prentice Hall Business Publishing, Accounting Information Systems, 9/e, by Bodnar/Hopwood 12 – 31 Relational Data Structures What is the relational model? It is a logical data structure that views the database as a collection of two-dimensional tables. There are no complicated pointers or lists.

33 2004 Prentice Hall Business Publishing, Accounting Information Systems, 9/e, by Bodnar/Hopwood 12 – 32 Relational Data Structures

34 2004 Prentice Hall Business Publishing, Accounting Information Systems, 9/e, by Bodnar/Hopwood 12 – 33 Relational Data Structures First normal form Second normal form Third normal form What are the three normal forms?

35 2004 Prentice Hall Business Publishing, Accounting Information Systems, 9/e, by Bodnar/Hopwood 12 – 34 Learning Objective 4 Explain the different methods of accessing files.

36 2004 Prentice Hall Business Publishing, Accounting Information Systems, 9/e, by Bodnar/Hopwood 12 – 35 Database Architecture: The Physical Level Indexed files Directly accessed files Sequentially accessed files

37 2004 Prentice Hall Business Publishing, Accounting Information Systems, 9/e, by Bodnar/Hopwood 12 – 36 Sequentially Accessed Files Sequential file organization is useful when batch processing is required. In a sequential access file, records can only be accessed in their predefined sequence.

38 2004 Prentice Hall Business Publishing, Accounting Information Systems, 9/e, by Bodnar/Hopwood 12 – 37 Indexed Files One important type of indexed file is an indexed-sequential file. An index file is one where an attribute has been extracted from the records and used to build a new file whose purpose is to provide an index to the original file.

39 2004 Prentice Hall Business Publishing, Accounting Information Systems, 9/e, by Bodnar/Hopwood 12 – 38 Indexed Files These files are frequently referred to as ISAM files. An indexed-sequential file is a sequential file that is stored on a DASD and is both indexed and physically sorted on the same field.

40 2004 Prentice Hall Business Publishing, Accounting Information Systems, 9/e, by Bodnar/Hopwood 12 – 39 Indexed Files An ISAM file structurally consists of three distinct areas: The index The prime area The overflow area How would a computer locate a file record whose key is 1002?

41 2004 Prentice Hall Business Publishing, Accounting Information Systems, 9/e, by Bodnar/Hopwood 12 – 40 Structure of an ISAM File Master Index Track Index Trackaddress Highest key on track Prime Area KeyData Record found Track index address Highest key Trackaddress Track address

42 2004 Prentice Hall Business Publishing, Accounting Information Systems, 9/e, by Bodnar/Hopwood 12 – 41 Directly Accessed Files Each record is assigned to a storage location that bears some relationship to the records key values. Most direct-access file systems convert a key to a storage location address. Direct-access files allow individual records to be almost instantly retrieved without the use of an index.

43 2004 Prentice Hall Business Publishing, Accounting Information Systems, 9/e, by Bodnar/Hopwood 12 – 42 Use of a Direct-Access File Datarecords Add remainder to displacement address (10) Filestoragearea Randomizingcomputation (÷ 7)

44 2004 Prentice Hall Business Publishing, Accounting Information Systems, 9/e, by Bodnar/Hopwood 12 – 43 Use of a Direct-Access File Remainderafterdivision by seven Displacementfactor (initial address of file area) KeyRecordRecordstorageaddress = Overflow Overflow

45 2004 Prentice Hall Business Publishing, Accounting Information Systems, 9/e, by Bodnar/Hopwood 12 – 44 Use of a Direct-Access File Range of randomizingcomputation Storage allocated for overflowrecords … Record 1 KEY 15* … Record 2 KEY 17 Record 3 KEY 11 …… Record 4 KEY 22 …ContentsAddress Overflowindicator

46 2004 Prentice Hall Business Publishing, Accounting Information Systems, 9/e, by Bodnar/Hopwood 12 – 45 Economic Relations between File Organization Techniques What is the activity ratio? It is the number of accessed records divided by the number of records in the file. The second economic consideration concerns response time. The basic economics of file processing are largely determined by the activity ratio.

47 2004 Prentice Hall Business Publishing, Accounting Information Systems, 9/e, by Bodnar/Hopwood 12 – 46 Economic Relations between File Organization Techniques It is the length of time the user must wait for the system to complete an operation. Response time is affected by the physical access time. Another factor that can affect response time is how data records are physically distributed on the disk. What is response time?

48 2004 Prentice Hall Business Publishing, Accounting Information Systems, 9/e, by Bodnar/Hopwood 12 – 47 Learning Objectives 5 and 6 Explain the benefits of database management systems. Describe the considerations that are appropriate to the design of computer-based files and databases.

49 2004 Prentice Hall Business Publishing, Accounting Information Systems, 9/e, by Bodnar/Hopwood 12 – 48 Database Management Systems and Databases in Practice All DBMS contain three common attributes for managing and organizing data. Database Management Systems (DBMS) are computer programs that enable a user to create and update files, to select and retrieve data, and to generate various outputs and reports.

50 2004 Prentice Hall Business Publishing, Accounting Information Systems, 9/e, by Bodnar/Hopwood 12 – 49 Database Management Systems and Databases in Practice Data description language (DDL) Data manipulation language (DML) Data query language (DQL) What are these attributes?

51 2004 Prentice Hall Business Publishing, Accounting Information Systems, 9/e, by Bodnar/Hopwood 12 – 50 Why Database Management Systems are Needed In the absence of integration, each type of accounting application such as sales, payroll, and receivables will maintain separate, independent data files and computer programs. DBMS integrate, standardize, and provide security for various accounting applications.

52 2004 Prentice Hall Business Publishing, Accounting Information Systems, 9/e, by Bodnar/Hopwood 12 – 51 Database Management Concepts Application One XYBA Application Two XYCD

53 2004 Prentice Hall Business Publishing, Accounting Information Systems, 9/e, by Bodnar/Hopwood 12 – 52 Database Management Concepts XYABCDDAYX XYAB Logical file 1 Application one Logical file 2 Application two XYCDDatabase dictionary and access codes Datamanipulationroutines Logical file 3 Security screened inquiry file Databasesystem

54 2004 Prentice Hall Business Publishing, Accounting Information Systems, 9/e, by Bodnar/Hopwood 12 – 53 Database Documentation and Administration The data dictionary is simply another file, sort of file of files, whose record occurrences consist of data item descriptions. Database dictionaries are used both alone and with DBMS to centralize, document, control, and coordinate the use of data within an organization.

55 2004 Prentice Hall Business Publishing, Accounting Information Systems, 9/e, by Bodnar/Hopwood 12 – 54 Data Dictionary Format Specifications Name Name Definition Definition Aliases AliasesCharacteristics Size Size Range of values Range of values Encoding Encoding Editing data Editing dataUtilization Owner Owner Where used Where used Security code Security code Last update Last update

56 2004 Prentice Hall Business Publishing, Accounting Information Systems, 9/e, by Bodnar/Hopwood 12– 55 End of Chapter 12


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