Ais Chapter Four

March 29, 2018 | Author: GeorgeRaafat | Category: Conceptual Model, Databases, Data Warehouse, Areas Of Computer Science, Technology


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Chapter 4Relational Databases Learning Objectives: - After studying this chapter you should be able t0: 1Explain the difference between database systems and file-based systems, using data warehouses as well as the advantages of database systems. 2- Explain the difference between logical and physical views of a database. 3- Explain fundamental concepts of database systems such as DBMS, schemas, the dictionary, and DBMS languages. 4- Explain database systems and the future of accounting. Objective 1: The Difference between Database Systems and File-based Systems, Using Data Warehouses for Business Intelligence as well as the Advantages of Database Systems. 1/1- Files versus databases: To appreciate the power of databases, it is important to understand how data are stored in computer systems. Figure 4-1, P. 107 shows a data hierarchy. Databases were developed to address the proliferation of master files. For many years, companies created new files and programs each time a need for information arose.  data is an organizational resource that is used by and managed for the entire organization. This proliferation created problems such as:  1.storing the same data in two or more master files. not just the originating department. This made it difficult to: ** integrate and update data. Figure 4-2. P. For Example. In the database approach.It also created problems because the data in the different files were inconsistent. and ** obtain an organization-wide view of data. 2.       . a customer’s address may have been correctly updated in the shipping master file but not the billing master file. 108 illustrates the differences between fileoriented systems and database systems. . . . . Data warehouses do not replace transaction processing databases.Using Data Warehouses for Business Intelligence:   Management must constantly reevaluate financial and operating performance in light of strategic goals and quickly alter plans as needed. and ** is used for analysis rather than transaction processing.1/2. they complement them by providing support for strategic decision making. Since strategic decision making requires access to large amount of historical data. . data warehouse:  A  ** contains both detailed and summarized data for a   number of years. organizations are building separate databases called data warehouses. and data mining. ..  There are two main techniques used in business intelligence: online analytical processing.Whereas transaction processing databases minimize redundancy and maximize the efficiency of updating them to reflect the results of current transactions.Since data warehouses are not used for transaction processing.  Using a data warehouse for strategic decision making is often referred to as business intelligence. . they are usually updated periodically rather than in real time. data warehouses are purposely redundant to maximize query efficiency. for grouping purchases by different items and by fiscal periods. 2. including artificial intelligence techniques such as neural networks. to “discover” unhypothesized relationships in the data.  For example.Data mining:  Data mining is using sophisticated statistical analysis.1. a manager may analyze supplier purchases for the last three years.Online analytical processing (OLAP):  Online analytical processing (OLAP) is using quires to guide the investigation of hypothesized relationships in data. .  For example. Finally. data mining techniques can identify previously unknown relationships in data that can be used in future promotions. It is also important to control access to the data warehouse. it is important to regularly backup copies of the data warehouse and store them securely.  Proper controls are needed to reap significant benefits from data warehousing.    . such as: Data validation controls are needed to ensure that data warehouse input is accurate. or auditing. and job skills master files.Data integration:   Master files are combined into large “pools” of data that many application programs can access. data processing. or evaluate the controls needed to ensure database integrity. An employee database that consolidates payroll.1/3. querying. manage. . Database systems provide organizations with the following benefits: 1.  Example.The Advantages of Database Systems:   Most accountants are involved with databases through data entry. They also develop. personnel. data redundancy and data inconsistencies are minimized. Databases are easily browsed to research a problem or obtain detailed information underlying a report.Minimal data redundancy and data inconsistencies:  Because data items are usually stored only once.  3.  4. .2.Data sharing:  Integrated data are more easily shared with authorized users.Data independence:   Because data and the programs that use them are independent of each other. each can be changed without the other. This facilitates programming and simplifies data management. Cross.5. .functional analysis:  In a database system. such as the association between selling costs and promotional campaigns . relationships. can be explicitly defined and used in the preparation of management reports. . the programmer must understand: ** the location and length of the fields needed. and current balance.In file-oriented systems.      Example. and ** the format of each field (alphanumeric or numeric). The process becomes more complex if data from several files are used. Suppose a programmer wants a report showing customer number. programmers must know the physical location and layout of records. credit limit. To write the program.Objective 2: Explain the difference between logical and physical views of a database. . shows a record layout of an accounts receivable file.  Figure 4-3.  The database approach provides two separate views of the data:  1.The logical view:  The logical view is how people conceptually organize and understand the data. Database systems overcome this problem by separating the storage of the data from the use of data elements. . a sales manager views all customer information as being stored in a table.  2.  For example.Physical view:  The physical view refers to how and where data are physically arranged and stored in the computer system. the dictionary. 3. 1- The conceptual-level schema:  The conceptual-level schema.Schemas: A schema describes the logical structure of a database.The internal-level schema.The conceptual-level schema.   . lists all data elements and the relationships among them. the organization wide view of the entire database. and DBMS languages:    3/1. 2.Objective 3.Explain fundamental concepts of database systems such as schemas.The external-level schema. There are three levels of schemas:  1. For example.  Each subschema can prevent access to those portions of the database that do not apply to it. 2.The external-level schema:  The external-level schema consists of the individual user views of portions of the database. the conceptual schema for the revenue cycle database contains data about:  customers.  cash receipts. each is tailored to the needs of different users or programs. and  inventory.  Subschemas are derived from the conceptual schema. each of which is referred to as a subschema. .  sales personnel.  sales. ** inventory quantities. ** current balances.     3. and ** prices. addresses. the sales order entry subschema includes data about: ** customer credit limits.The internal-level schema:  The internal-level schema. is a lower-level view of the database. It describes how the data are stored and accessed including record layouts.  It would not include the cost of inventory or bank account balances. . definitions. and indexes. Example. Inputs of data dictionary:    inputs include: New or deleted data elements. changes in data element names .3/2. description. there is a record in the dictionary describing it. or use. . 1.Data Dictionary: A data dictionary contains information about the structure of the database.  For each data element stored in the database.  DBMS maintains the data dictionary. and users such as: 1. and ** as a part of audit trail. designers.data elements used by a user. These reports are used for: ** System documentation. . ** Database design and implementation.synonyms for the data elements in a file. 2.Programs or reports using a data item. and 3.2- Outputs of data dictionary: Outputs include reports for programmers. .The data definition language (DDL). and ** specifies records or fields security constraints.The data manipulation language (DML). 2.The data query language (DQL). ** creates the database.DBMS Languages:  A DBMS has several languages such as: 1. 1.3/3. ** describes logical views for each user.The data definition language (DDL): ** builds the data dictionary.The data definition language (DDL): . 3. The data manipulation language (DML):  The data manipulation language (DML) changes database content. and display data. • • . and deletions. sort.2.The data query language (DQL): • The data query language (DQL) contains powerful. • Notes: • A report writer simplifies report creation. The DQL and report writer are available to users. easy-t0-use commands that enable users to retrieve. including data elements updates. The DDL and DML should be restricted to authorized administrators and programmers. order. insertions. 3. For example: ** In the future. ** Users would be free to analyze the raw data however they see fit. .A significant advantage of database systems is the ability to create ad hoc queries to provide the information needed for decision making.Database systems have the potential to alter    external reporting. companies may make a copy of the company’s financial database available to external users in lieu of the traditional financial statements.Objective 4: Explain database systems and the future of accounting: . . .  For example.No longer is financial information available only in predefined formats and at specified times.  Finally. tables storing information about assets can include columns not only for historical costs but also for: ** current replacement costs. managers will no longer be forced to look at data in ways predefined by accountants.Thus.  . powerful and easy-to-use relational database query languages can find and prepare the information management needs. relational DBMSs are capable of integrating financial and operational data. and ** market values. when they want it.  Instead. Such participation is important for: ** ensuring that adequate controls are included in those systems to safeguard the data. and ** ensure the reliability of the information produced. For example. giving managers a richer set of data for decision making.  NOTE: Accountants must understand database systems so they can help design and use the AISs in the future.      End of Chapter Four . customer satisfaction data could be stored in the database.
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