Syllabus Focus: Unit 2 Module 1 Content 4 - 5

Specific Objective 4: Explain the advantages of using a database approach compared to using traditional file processing;Content: Advantages including speed, efficiency, cost; data quality: completeness, validity, consistency, timeliness and accuracy; data handling, data processing.

explain the advantages of using a database approach compared to using traditional file processing;

Advantages including speed, efficiency, cost; data quality: completeness, validity, consistency, timeliness and accuracy; data handling, data processing.

What are Traditional File Processing systems?

Traditional file based system is basically a file based system, in which we manually or through computer handle the database such as updating, inserting, deletion or adding new files to database, etc.

There are several advantages of TFBS (Traditional File Based System):

1. No need of external storage 2. No need of highly technical person to handle the database.

3. Processing speed is high as compare to DBMS.

TFBS has also some disadvantages:

1. Provide less security. 2. Redundancy is high

3. Less integrity

4. High complexity in updating of database records

http://wiki.answers.com/Q/What_is_a_traditional_File-Based_System

What is a Database?

A Computer Database is a structured collection of records or data that is stored in a computer system. The structure is achieved by organizing the data according to a database model. The model in most common use today is the relational model. Other models such as the hierarchical model and the network model use a more explicit representation of relationships (see below for explanation of the various database models).

A computer database relies upon software to organize the storage of data. This software is known as a database management system (DBMS). Database management systems are categorized according to the database model that they support. The model tends to determine the query languages that are available

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to access the database. A great deal of the internal engineering of a DBMS, however, is independent of the data model, and is concerned with managing factors such as performance, concurrency, integrity, and recovery from hardware failures. In these areas there are large differences between products.

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What is a Database Management System?

A Database Management System (DBMS) is computer software designed for the purpose of managing databases based on a variety of data models.

http://en.wikipedia.org/wiki/Database_management_system

Comparison of Databases and Traditional File Processing System

If some major changes were to be made to the data, the application programs may need to be rewritten. In a database system, the database management system provides the interface between the application programs and the data. When changes are made to the data representation, the metadata maintained by the DBMS is changed but the DBMS continues to provide data to application programs in the previously used way. The DBMS handles the task of transformation of data wherever necessary.

This independence between the programs and the data is called data independence. Data independence is important because every time some change needs to be made to the data structure, the programs that were being used before the change would continue to work. To provide a high degree of data independence, a DBMS must include a sophisticated metadata management system.

In DBMS, all files are integrated into one system thus reducing redundancies and making data management more efficient. In addition, DBMS provides centralized control of the operational data.

Some of the advantages of data independence, integration and centralized control are:

1. Redundancies and inconsistencies can be reduced (Efficiency)

In conventional data systems, an organization often builds a collection of application programs often created by different programmers and requiring different components of the operational data of the organization. The data in Conventional Data Systems (Traditional File Management System) is often not centralised. Some applications may require data to be combined from several systems. These several systems could well have data that is redundant as well as inconsistent (that is, different copies of the same data may have different values). Data inconsistencies are often encountered in everyday life. For example, we have all come across situations when a new address is communicated to an organization that we deal with (e.g. a bank, or Telecom, or a gas company), we find that some of the communications from that organization are received at the new address while others continue to be mailed to the old address. Combining all the data in a database would involve reduction in redundancy as well as inconsistency. It also is likely to reduce the costs for collection, storage and updating of data.

2. Better service to the Users (Efficiency)

A DBMS is often used to provide better service to the users. In conventional systems, availability of information is often poor since it normally is difficult to obtain information that the existing systems were not designed for. Once several conventional systems are combined to form one centralized data

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base, the availability of information and its up-to-datedness is likely to improve since the data can now be shared and the DBMS makes it easy to respond to unforeseen information requests.

Centralizing the data in a database also often means that users can obtain new and combined information that would have been impossible to obtain otherwise. Also, use of a DBMS should allow users that do not know programming to interact with the data more easily.

The ability to quickly obtain new and combined information is becoming increasingly important in an environment where various levels of governments are requiring organizations to provide more and more information about their activities. An organization running a conventional data processing system would require new programs to be written (or the information compiled manually) to meet every new demand.

3. Flexibility of the system is improved (Efficiency)

Changes are often necessary to the contents of data stored in any system. These changes are more easily made in a database than in a conventional system in that these changes do not need to have any impact on application programs.

4. Cost of developing and maintaining systems is lower (Cost)

It is much easier to respond to unforeseen requests when the data is centralized in a database than when it is stored in conventional file systems. Although the initial cost of setting up of a database can be large, one normally expects the overall cost of setting up a database and developing and maintaining application programs to be lower than for similar service using conventional systems since the productivity of programmers can be substantially higher in using non-procedural languages that have been developed with modern DBMS than using procedural languages.

5. Standards can be enforced (Data Quality)

Since all access to the database must be through the DBMS, standards are easier to enforce. Standards may relate to the naming of the data, the format of the data, the structure of the data etc. This might not be so when using Traditional File Storage Systems.

6. Security can be improved

In conventional systems, applications are developed in an ad hoc manner. Often different systems of an organization would access different components of the operational data. In such an environment, enforcing security can be quite difficult.

Setting up of a database makes it easier to enforce security restrictions since the data is now centralized. It is easier to control that has access to what parts of the database. However, setting up a database can also make it easier for a determined person to breach security. We will discuss this in the next section.

7. Integrity can be improved (Validity)

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Since the data of the organization using a database approach is centralized and would be used by a number of users at a time, it is essential to enforce integrity controls.

Integrity may be compromised in many ways. For example, someone may make a mistake in data input and the salary of a full-time employee may be input as $4,000 rather than $40,000. A student may be shown to have borrowed books but has no enrolment. Salary of a staff member in one department may be coming out of the budget of another department.

If a number of users are allowed to update the same data item at the same time, there is a possibility that the result of the updates is not quite what was intended. For example, in an airline DBMS we could have a situation where the number of bookings made is larger than the capacity of the aircraft that is to be used for the flight. Controls therefore must be introduced to prevent such errors to occur because of concurrent updating activities. However, since all data is stored only once, it is often easier to maintain integrity than in conventional systems.

8. Enterprise requirements can be identified (Data Handling)

All enterprises have sections and departments and each of these units often consider the work of their unit as the most important and therefore consider their needs as the most important. Once a database has been set up with centralized control, it will be necessary to identify enterprise requirements and to balance the needs of competing units. It may become necessary to ignore some requests for information if they conflict with higher priority needs of the enterprise.

9. Data model must be developed (Data Handling)

Perhaps the most important advantage of setting up a database system is the requirement that an overall data model for the enterprise be built. In conventional systems, it is more likely that files will be designed as needs of particular applications demand. The overall view is often not considered. Building an overall view of the enterprise data, although often an expensive exercise is usually very cost-effective in the long term.

http://www.cs.jcu.edu.au/Subjects/cp1500/1998/Lecture_Notes/databases/dbms_adv.html

10. Faster response to query processing – provision of results of searches (Timeliness)

Databases today allows users to retrieve information stored across many database tables, doing this by creating relationships between tables and allow multiple sets of criteria to be used to search field (s) in tables and extract the results. Databases over their conventional filing systems allows for quicker updating of multiple records based on a criteria or set of criterias based on the use of Update Queries.

Speed: Databases allows records to be retrieved at high speed allowing for greater information retrieval. With Databases, the database can be powered with several criterias that can be executed together (compulsory criteria selection) or separately (hierarchical criteria selection). Database criterias can extract data from several huge database tables consisting of thousands of records, and return the specific data required quickly in order to make decisions.

Completeness:

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With databases, information regarding to one item can be pulled together from several database tables using joins (relationships) and create a move satisfying view of all information about that item. With this feature, databases are able to give a better cross sectional view of data. Data can be combined from a Customer table, the Orders table, the Billings table and the Delivery table.

Consistency:

With Databases, changes made in the main tables are automatically reflected across all queries and reports and Database allows for greater consistency in data entry. With the use of drop list in database allows you to more accurately enter the same group of data (i.e. Model of Cars – Toyota, Suzuki, Ford, Honda, BMW, Mercedes, etc.).

Additional discussion:

Controlling redundancy; providing storage structure for efficient query processing. Restricting unauthorized users; providing concurrency; Providing backup and recovery; enforcing integrity constraints.

Disadvantages of Databases

A database system generally provides on-line access to the database for many users. In contrast, a conventional system is often designed to meet a specific need and therefore generally provides access to only a small number of users. Because of the larger number of users accessing the data when a database is used, the enterprise may involve additional risks as compared to a conventional data processing system in the following areas.

1. Confidentiality, privacy and security – due to the high concerns of these factors and the threat post by hackers and other harmful users, a large amount of money is allocated to cover the cost associated with maintaining databases to provide for these features. Due to the high cost of database maintenance, at times the cost is passed onto the customer or included in the service or product cost.

2. Data quality – as to who has the right to maintain the data and to periodically clean the database, this can pose a significant challenge. One would have to ensure that they run several Data Cleansing software tool and use this in ensuring that the quality of data stored can be improved.

3. Data integrity – not at all times are managers able to ensure that the data stored is accurate and properly stored. When one is to question the data updating capacity of a DBMS, then the integrity of the data generated or stored is also an issue.

4. Enterprise vulnerability may be higher – databases are normally high cost investments for organizations such as banks, insurance companies, cable companies, weather monitoring stations, etc. How would a company survive the attack on its database is not a guarantee that this would not severely affect their operations and may even render the company wounded from operating.

5. The cost of using DBMS – not just to collect, store and run queries are what databases are used for, but they are also used to ensure the company can operate. Other costs to be considered include security, management controls, concurrency control (record, file, table locking – Shared and Exclusive Locks on Database Records, table, etc.).

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Confidentiality, Privacy and Security

When information is centralised and is made available to users from remote locations, the possibilities of abuse are often more than in a conventional data processing system. To reduce the chances of unauthorised users accessing sensitive information, it is necessary to take technical, administrative and, possibly, legal measures.

Most databases store valuable information that must be protected against deliberate trespass and destruction.

Data Quality

Since the database is accessible to users remotely, adequate controls are needed to control users updating data and to control data quality. With increased number of users accessing data directly, there are enormous opportunities for users to damage the data. Unless there are suitable controls, the data quality may be compromised.

Data Integrity

Since a large number of users could be using a database concurrently, technical safeguards are necessary to ensure that the data remain correct during operation. The main threat to data integrity comes from several different users attempting to update the same data at the same time. The database therefore needs to be protected against inadvertent changes by the users.

Enterprise Vulnerability

Centralising all data of an enterprise in one database may mean that the database becomes an indispensible resource. The survival of the enterprise may depend on reliable information being available from its database. The enterprise therefore becomes vulnerable to the destruction of the database or to unauthorised modification of the database.

The Cost of using a DBMS

Conventional data processing systems are typically designed to run a number of well-defined, preplanned processes. Such systems are often "tuned" to run efficiently for the processes that they were designed for.

Additional Issues:Centralization: That is use of the same program at a time by many users sometimes lead to loss of some data; High cost of software.

Additional Content:

Although the conventional systems are usually fairly inflexible in that new applications may be difficult to implement and/or expensive to run, they are usually very efficient for the applications they are designed for.

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The database approach on the other hand provides a flexible alternative where new applications can be developed relatively inexpensively. The flexible approach is not without its costs and one of these costs is the additional cost of running applications that the conventional system was designed for. Using standardised software is almost always less machine efficient than specialised software.

We now discuss a conceptual framework for a DBMS. Several different frameworks have been suggested over the last several years. For example, a framework may be developed based on the functions that the various components of a DBMS must provide to its users. It may also be based on different views of data that are possible within a DBMS. We consider the latter approach.

A commonly used view of data approach is the three-level architecture suggested by ANSI/SPARC (American National Standards Institute/Standards Planning and Requirements Committee). ANSI/SPARC produced an interim report in 1972 followed by a final report in 1977. The reports proposed an architectural framework for databases. Under this approach, a database is considered as containing data about an enterprise. The three levels of the architecture are three different views of the data:

1. External - individual user view 2. Conceptual - community user view 3. Internal - physical or storage view

The three level database architecture allows a clear separation of the information meaning (conceptual view) from the external data representation and from the physical data structure layout. A database system that is able to separate the three different views of data is likely to be flexible and adaptable. This flexibility and adaptability is data independence that we have discussed earlier.

We now briefly discuss the three different views.

The External Level is the view that the individual user of the database has. This view is often a restricted view of the database and the same database may provide a number of different views for different classes of users. In general, the end users and even the applications programmers are only interested in a subset of the database. For example, a department head may only be interested in the departmental finances and student enrolments but not the library information. The librarian would not be expected to have any interest in the information about academic staff. The payroll office would have no interest in student enrolments.

The Conceptual View is the information model of the enterprise and contains the view of the whole enterprise without any concern for the physical implementation. This view is normally more stable than the other two views. In a database, it may be desirable to change the internal view to improve performance while there has been no change in the conceptual view of the database. The conceptual view is the overall community view of the database and it includes all the information that is going to be represented in the database. The conceptual view is defined by the conceptual schema which includes definitions of each of the various types of data.

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The Internal View is the view about the actual physical storage of data. It tells us what data is stored in the database and how. At least the following aspects are considered at this level:

1. Storage allocation e.g. B-trees, hashing etc. 2. Access paths e.g. specification of primary and secondary keys, indexes and pointers and sequencing. 3. Miscellaneous e.g. data compression and encryption techniques, optimisation of the internal structures.

Efficiency considerations are the most important at this level and the data structures are chosen to provide an efficient database. The internal view does not deal with the physical devices directly. Instead it views a physical device as a collection of physical pages and allocates space in terms of logical pages.

The separation of the conceptual view from the internal view enables us to provide a logical description of the database without the need to specify physical structures. This is often called physical data independence. Separating the external views from the conceptual view enables us to change the conceptual view without affecting the external views. This separation is sometimes called logical data independence.

Assuming the three level view of the database, a number of mappings are needed to enable the users working with one of the external views. For example, the payroll office may have an external view of the database that consists of the following information only:

1. Staff number, name and address. 2. Staff tax information e.g. number of dependents. 3. Staff bank information where salary is deposited. 4. Staff employment status, salary level, leaves information, etc.

The Conceptual View of the database may contain academic staff, general staff, casual staff etc. A mapping will need to be created where all the staff in the different categories are combined into one category for the payroll office. The conceptual view would include information about each staff's position, the date employment started, full-time or part-time, etc. This will need to be mapped to the salary level for the salary office. Also, if there is some change in the conceptual view, the external view can stay the same if the mapping is changed.

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Figure 1.1 DBMS Architecture

Role of the Database Administrator

The database will be able to meet the demands of various users in the organization effectively only if it is maintained and managed properly. Usually a person (or a group of persons) centrally located, with an overall view of the database, is needed to keep the database running smoothly. Such a person is called the Database Administrator (DBA).

The DBA would normally have a large number of tasks related to maintaining and managing the database. These tasks would include the following:

1. Deciding and Loading the Database Contents - The DBA in consultation with senior management is normally responsible for defining the conceptual schema of the database. The DBA would also be responsible for making changes to the conceptual schema of the database if and when necessary.

2. Assisting and Approving Applications and Access - The DBA would normally provide assistance to end-users interested in writing application programs to access the database. The DBA would also approve or disapprove access to the various parts of the database by different users.

3. Deciding Data Structures - Once the database contents have been decided, the DBA would normally make decisions regarding how data is to be stored and what indexes need to be maintained. In addition, a DBA normally monitors the performance of the DBMS and makes changes to data structures if the performance justifies them. In some cases, radical changes to the data structures may be called for.

4. Backup and Recovery - Since the database is such a valuable asset, the DBA must make all the efforts possible to ensure that the asset is not damaged or lost. This normally requires a DBA to ensure that regular backups of a database are carried out and in case of failure (or some other disaster like fire or flood), suitable recovery procedures are used to bring the database up with as little down time as possible.

5. Monitor Actual Usage - The DBA monitors actual usage to ensure that policies laid down regarding use of the database are being followed. The usage information is also used for performance tuning.

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Figure 1.2 System Architecture of a DBMS

http://www.cs.jcu.edu.au/Subjects/cp1500/1998/Lecture_Notes/databases/

References:

1. J. P. Fry and E. H. Sibley (1976), "Evolution of Data-Base Management Systems", ACM Computing Surveys, 8, March 1976, pp. 7-42.

2. D. A. Jardine, ed. (1977), "The ANSI/SPARC DBMS Model", North-Holland. 3. D. Tsichritzis and A. Klug, Eds. (1978), "The ANSI/X3/SPARC Framework", Info. Systems, Vol 3,

No 3, 1978.

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SECTION 2: Types and organizational of files and databases

describe the different types and organization of files and databases;

File types including master and transaction files; file organization including serial, sequential, random or direct, indexed sequential database types including personal, workgroup, department and enterprise databases; database organization including hierarchical, relational, network and object-oriented.

FILE TYPES

Master File

A master file or master table contains a group of common records. Item Data, Customer Data, and Supplier Data are examples of tables.www.ssgweb.com/CourseTerms.cfm

Contains information about an organization’s business situation. Most transactions and databases are stored in the master file. www.nationmaster.com/encyclopedia/Transaction-Processing-System

File maintained by the Contractor that contains all essential account information.www.gsa.gov/gsa/cm_attachments/GSA_BASIC/GLOSSARY_R2-v-h8-u_0Z5RDZ-i34K-pR.doc

A file of relatively permanent data or information that is updated periodically.highered.mcgraw-hill.com/sites/0073010847/student_view0/chapter8/key_terms.html

A file of data which is the principal source of information for a job which is updated or amended as necessary. www.nursing.bcs.org/inftouch/vol1/glossv1.html

(computer science) a computer file that is used as the authority in a given job and that is relatively permanent wordnet.princeton.edu/perl/webwn

Transaction File

It is the collection of transaction records. It helps to update the master file and also serves as audit trails and transaction history. en.wikipedia.org/wiki/Transaction_Processing_System

(computer science) a computer file containing relatively transient data about a particular data processing task wordnet.princeton.edu/perl/webwn

A collection of transaction records. The data in transaction files is used to update the master files, which contain the data about the subjects of the organization (customers, employees, vendors, etc.).

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Transaction FileOld

Master File

NewMaster File

UPDATE

Transaction files also serve as audit trails and history for the organization. Where before they were transferred to offline storage after some period of time, they are increasingly being kept online for routine analysis

FILE ORGANIZATION

Serial

This means ...start at the beginning of the file and access each record in turn until the one needed is found. If files are stored on magnetic tape then serial access is the only method of access.

Sequential

A group of elements (e.g. data in a memory array or a disk file or on a tape) is accessed in a predetermined, ordered sequence. Sequential access is sometimes the only way of accessing the data, for example if it is on a tape. It may also be the access method of choice, for example if we simply want to process a sequence of data elements in order.

Random (or Direct)

The computer can calculate (from the key field) where the record is stored in the file, and can then access the record directly from that position. Direct access can only be used if files are stored on media such as disk, CD, DVD. Direct access of records will generally be much faster than Serial Access. Direct access is also known as random access.

Useful Link: http://www.theteacher99.btinternet.co.uk/theteacher/gcse/newgcse/others/file_gens.htm

Indexed Sequential

Indexed Sequential files are important for applications where data needs to be accessed randomly using the index. For example when the whole of the file is processed to produce pay slips at the end of the month. An Indexed Sequential file can only be stored on a random access deviceeg magnetic disc, CD.

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DATABASE TYPES

Personal – used for recording self information and for one’s own access. A database created to store phone contacts and addresses and friends would be a good example.

Workgroup – used by teams working on tasks that needs access to the same data. Maybe the building team of a major works projects have contractors, builders and engineers using the same database to update each other on the status of their work.

Department – use by a unit in an organization which provides some functional application of the data in the department’s domain. The marketing department of an insurance company could have a database of possible clients who can be contacted to discuss possible choices of policy that are offered.

Enterprise - Centralized data that is shared by many users throughout the organization. The information shared across all branches of a bank on its customers’ accounts and allows any branch to post a transaction to the customer file and eventual update the master file stored in a centralised or distributed manner.

DATBASE ORGANIZATION

Hierarchical

In a hierarchical data model, data is organized into a tree-like structure. The structure allows repeating information using parent/child relationships: each parent can have many children but each child only has one parent. All attributes of a specific record are listed under an entity type. In a database, an entity type is the equivalent of a table; each individual record is represented as a row and an attribute as a column. Entity types are related to each other using 1: N mapping, also known as one-to-many relationships.

http://en.wikipedia.org/wiki/Hierarchical_model

An example of a hierarchical data model would be if an organization had records of employees in a table (entity type) called "Employees". In the table there would be attributes/columns such as First Name, Last Name, Job Name and Wage. The company also has data about the employee’s children in a separate table called "Children" with attributes such as First Name, Last Name, and date of birth. The Employee table represents a parent segment and the Children table represents a Child segment. These two segments form a hierarchy where an employee may have many children, but each child may only have one parent.

Relational

The relational model for database management is a database model based on first-order predicate logic, first formulated and proposed in 1969 by Edgar Codd.[1] [2] [3]

Its core idea is to describe a database as a collection of predicates over a finite set of predicate variables, describing constraints on the possible values and combinations of values. The content of the database at any given time is a finite model (logic) of the database, i.e. a set of relations, one per predicate variable, such that all predicates are satisfied. A request for information from the database (a database query) is also a predicate.

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The purpose of the relational model is to provide a declarative method for specifying data and queries: we directly state what information the database contains and what information we want from it, and let the database management system software take care of describing data structures for storing the data and retrieval procedures for getting queries answered.

Object-oriented

An object-relational database (ORD) or object-relational database management system (ORDBMS) is a database management system (DBMS) similar to a relational database, but with an object-oriented database model: objects, classes and inheritance are directly supported in database schemas and in the query language. In addition, it supports extension of the data model with custom data-types and methods.

One aim for this type of system is to bridge the gap between conceptual data modeling techniques such as Entity-relationship diagram (ERD) and object-relational mapping (ORM), which often use classes and inheritance, and relational databases, which do not directly support them.

Another, related, aim is to bridge the gap between relational databases and the object-oriented modeling techniques used in programming languages such as Java, C++ or C#. However, a more popular alternative for achieving such a bridge is to use standard relational database systems with some form of ORM software.

Network

The network model is a database model conceived as a flexible way of representing objects and their relationships. Its original inventor was Charles Bachman, and it was developed into a standard specification published in 1969 by the CODASYL Consortium. Where the hierarchical model structures data as a tree of records, with each record having one parent record and many children, the network model allows each record to have multiple parent and child records, forming a lattice structure.

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