2. Accounting Information Systems, 1st Edition
Data and Databases
Accounting Information Systems, 1st Edition

3. Study Objectives The need for data collection and storage
Methods of storing data and the interrelationship between storage and processing
The differences between batch processing and real-time processing
The importance of databases and the historical progression from flat-file databases to relational databases
The need for normalization of data in a relational database
Data warehouse and the use of a data warehouse to analyze data
The use of OLAP and data mining as analysis tools
Distributed databases and advantages of the use of distributed data
Controls for Data and Databases
Ethical issues related to data collection and storage, and their use in IT systems
1. On the topic, “Challenges Facing Financial Accounting,” what did the AICPA Special Committee on Financial Reporting suggest should be included in future financial statements?
Non-financial Measurements (customer satisfaction indexes, backlog information, and reject rates on goods purchases).
Forward-looking Information
Soft Assets (a company’s know-how, market dominance, marketing setup, well-trained employees, and brand image).
Timeliness (no real time financial information)

4. The Need for Data Collection and Storage
Data are the set of facts collected from transactions, whereas information is the interpretation of data that have been processed.
Main reasons to store transaction data:
To complete transactions from beginning to end.
To follow up with customers or vendors and to expedite future transactions.
To create accounting reports and financial statements.
To provide feedback to management.
SO 1 The need for data collection and storage

5. The Need for Data Collection and Storage
Typical storage and processing techniques:
The storage media types for data: sequential and random access
Methods of processing data: batch and real time
Databases and relational databases
Data warehouses, data mining, and OLAP
Distributed data processing and distributed databases
SO 1 The need for data collection and storage

6. The Need for Data Collection and Storage
Concept Check
Which of the following best describes the relationship between data and information?
a. Data is interpreted information.
b. Information is interpreted data.
c. Data is more useful than information in decision making.
d. Data and information are not related.
SO 1 The need for data collection and storage

7. Storing and Accessing Data
Data Storage Terminology
Exhibit 13-1
Data Hierarchy
Character
Field
Record
File
Database
SO 2 Methods of storing data and the interrelationship between storage and processing

8. Storing and Accessing Data
Data Storage Media
Magnetic tape
Sequential access
Early Days of Mainframe Computers
Modern IT Systems
Random Access
SO 2 Methods of storing data and the interrelationship between storage and processing

9. Storing and Accessing Data
Concept Check
A character is to a field as
a. Water is to a pool.
b. A pool is to a swimmer.
c. A pool is to water.
d. A glass is to water.
SO 2 Methods of storing data and the interrelationship between storage and processing

10. Storing and Accessing Data
Concept Check
Magnetic tape is a form of
a. Direct access media.
b. Random access media.
c. Sequential access media.
d. Alphabetical access media.
SO 2 Methods of storing data and the interrelationship between storage and processing

11. Data Processing Techniques
Real-time Processing
Batch Processing
Exhibit 13-2
Comparison of Batch and Real-Time Processing
SO 3 The differences between batch processing and real-time processing

12. Data Processing Techniques
Concept Check
Which of the following is not an advantage of using real-time data processing?
Quick response time to support timely record keeping and customer satisfaction
b. Efficiency for use with large volumes of data.
c. Provides for random access of data.
d. Improved accuracy due to the immediate recording of transactions.
SO 3 The differences between batch processing and real-time processing

13. Databases
Data stored in a form that allows the data to be easily accessed, retrieved, manipulated, and stored.
Exhibit 13-3
Traditional File-Oriented Approach
Data redundancy
Concurrency
SO 4 The importance of databases and the historical progression from flat-file databases to relational databases

14. Databases
Exhibit 13-3
Database Approach
Relationships
One-to-One
One-to-Many
Many-to-Many
Database Management System (DBMS) is software that manages the database and controls the access and use of data by individual users and applications.
SO 4 The importance of databases and the historical progression from flat-file databases to relational databases

15. The History of Databases
Flat File Database Model
Exhibit 13-4
Database Table
1950s and 1960s
Text format, sequential order
Sequential processing
Large volumes of similar transactions
Single record not easily retrieved or stored
SO 4 The importance of databases and the historical progression from flat-file databases to relational databases

16. The History of Databases
Hierarchical Database Model
Inverted tree structure
Parent–child, represent one-to-many relationships
Record pointer
Exhibit 13-5
Linkages in a Hierarchical Database
SO 4 The importance of databases and the historical progression from flat-file databases to relational databases

17. The History of Databases
Network Database Model
Inverted tree structure
More complex relationship linkages by use of shared branches
Not very popular, rarely used
SO 4 The importance of databases and the historical progression from flat-file databases to relational databases

18. The History of Databases
Relational Database Model
Developed in 1969
Stores data in two-dimensional tables
Most widely used database structure today
Examples include; IBM DB2, Oracle Database, and Microsoft Access
SO 4 The importance of databases and the historical progression from flat-file databases to relational databases

19. Concept Check Databases a. attributes. b. data redundancy.
If a company stores data in separate files in its different departmental locations and is able to update all files simultaneously, it would not have problems with
a. attributes.
b. data redundancy.
c. industrial espionage.
d. concurrency.
SO 4 The importance of databases and the historical progression from flat-file databases to relational databases

20. Concept Check Databases a. flat file database.
When the data contained in a database are stored in large, two-dimensional tables, the database is referred to as a
a. flat file database.
b. hierarchical database.
c. network database.
d. relational database.
SO 4 The importance of databases and the historical progression from flat-file databases to relational databases

21. Concept Check Databases a. Network. b. Hierarchical. c. Relational.
Database management systems are categorized by the data structures they support. In which type of database management system is the data arranged in a series of tables?
a. Network.
b. Hierarchical.
c. Relational.
d. Sequential.
SO 4 The importance of databases and the historical progression from flat-file databases to relational databases

22. The Need for Normalized Data
Relational databases consist of several small tables. Small tables can be joined in ways that represent relationships among the data.
Exhibit 13-6
Relational Database in Microsoft Access
Bolded field is the primary key.
SO 5 The need for normalization of data in a relational database

23. The Need for Normalized Data
Relational database has flexibility in retrieving data. Structured query language (SQL) has become the industry standard.
Exhibit 13-7
Relational Database in Microsoft Access
SELECT Customers.CustomerID, Customers.CompanyName,
Orders.OrderID, Orders.ShippedDate FROM Customers INNER
JOIN Orders ON Customers.CustomerID Orders.CustomerID;
SO 5 The need for normalization of data in a relational database

24. The Need for Normalized Data
The process of converting data into tables that meet the definition of a relational database is called data normalization.
Seven rules of data normalization, additive.
Most relational databases are in third normal form.
First three rules of data normalization are:
Eliminate repeating groups
Eliminate redundant data
Eliminate columns not dependent on primary key.
SO 5 The need for normalization of data in a relational database

25. The Need for Normalized Data
Trade-offs in Database Storage
Relational database
Not most efficient way to store data that will be used in other ways.
Most organizations are willing to accept less transaction processing efficiency for better query opportunities.
SO 5 The need for normalization of data in a relational database

26. The Need for Normalized Data
Concept Check
Which of the following statements is not true with regard to a relational database?
a. It is flexible and useful for unplanned, ad hoc queries.
b. It stores data in tables.
c. It stores data in a tree formation.
d. It is maintained on direct access devices.
SO 5 The need for normalization of data in a relational database

27. Use of a Data Warehouse to Analyze Data
Management often needs data from several fiscal periods from across the whole organization.
Exhibit 13-8
The Data Warehouse and Operational Databases
SO 6 Data warehouse and the use of a data warehouse to analyze data

28. Use of a Data Warehouse to Analyze Data
Management often needs data from several fiscal periods from across the whole organization.
Build the data warehouse
Identify the data
Standardize the data
Cleanse, or scrub, the data
Upload the data
SO 6 Data warehouse and the use of a data warehouse to analyze data

29. Use of a Data Warehouse to Analyze Data
Concept Check
A collection of several years’ nonvolatile data used to support strategic decision-making is a(n)
a. operational database.
b. data warehouse.
c. data mine.
d. what-if simulation.
SO 6 Data warehouse and the use of a data warehouse to analyze data

30. Data Analysis Tools
Data mining is the process of searching for identifiable patterns in data that can be used to predict future behavior.
OLAP is a set of software tools that allow online analysis of the data within a data warehouse. Analytical methods in OLAP usually include:
Drill down
Consolidation
Pivoting
Time series analysis
Exception reports
What-if simulations
SO 7 The use of OLAP and data mining as analysis tools

31. Concept Check Data Analysis Tools
Data mining would be useful in all of the following situations except
a. identifying hidden patterns in customers’ buying habits.
b. assessing customer reactions to new products.
c. determining customers’ behavior patterns.
d. determining customers’ behavior patterns.
SO 7 The use of OLAP and data mining as analysis tools

32. Distributed Data Processing
Early days
Centralized processing
Centralized databases
Today’s IT Environment
Distributed data processing (DDP)
Distributed databases (DDB)
SO 8 Distributed databases and advantages of the use of distributed data

33. Distributed Data Processing
Distributing the processing and data offers the following advantages:
Reduced hardware cost
Improved responsiveness
Easier incremental growth
Increased user control and user involvement
Automatic integrated backup
The most popular type of distributed system is a client/server system.
SO 8 Distributed databases and advantages of the use of distributed data

34. Distributed Data Processing
Concept Check
A set of small databases where data are collected, processed, and stored on multiple computers within a network is a
a. Centralized database.
b. Distributed database.
c. Flat file database.
d. High-impact process.
SO 8 Distributed databases and advantages of the use of distributed data

35. IT Controls for Data and Databases
To ensure integrity (completeness and accuracy) of data in the database, IT application controls should be used. These controls are
input,
processing, and
output controls such as
data validation,
control totals and reconciliation, and
reports that are analyzed by managers.
SO 9 Controls for data and databases

36. Ethical Issues Related to Data Collection
Ethical Responsibilities of the Company
Data collected and stored in databases in many instances consist of information that is private between the company and its customer.
Ten privacy practices for online companies:
Management
Notice
Choice and consent
Collection
Use and retention
Access
Disclosure to third parties
Security for privacy
Quality
Monitoring and enforcement
SO 10 Ethical issues related to data collection and storage, and their use in IT systems

37. Ethical Issues Related to Data Collection
Ethical Responsibilities of Employees
Employees have an ethical obligation to avoid misuse of any private or personal data about customers.
There are no specific IT controls that would always prevent authorized employees from disclosing private information.
SO 10 Ethical issues related to data collection and storage, and their use in IT systems

38. Ethical Issues Related to Data Collection
Ethical Responsibilities of Customers
Customers have an obligation to
provide accurate and complete information.
keep any known company information confidential.
avoid improper use of data that they gain from accessing a database as a customer.
SO 10 Ethical issues related to data collection and storage, and their use in IT systems

39. Ethical Issues Related to Data Collection
Concept Check
Each of the following is an online privacy practice recommended by the AICPA Trust Principles Privacy Framework except:
a. Redundant data should be eliminated from the database.
b. Notification of privacy policies should be given to customers.
Private information should not be given to third parties without the customer’s consent
d. All of the above.
SO 10 Ethical issues related to data collection and storage, and their use in IT systems

40. Copyright
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