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State main categories of data models.

Conceptual models and Logical models are the two main categories of data models.


How are computers useful in processing the accounting data?

1. Reality: Reality refers to some aspect of the real world situation, for which database is to be designed. For example, in the case of a doctor, database is created of the patients with respect to their ailments, treatment given and so on. Reality is a real world situation. In the context of accounting, accounting itself is a reality that is to be expressed. For example, a transaction is documented using a voucher a voucher that is serially numbered and dated, and bears account name along with its code for the debit and credit entry. Account codes are given to each account head according to the grouping of the account head, ie., asset, liability, expense and income. Evidences of transactions, ie., bills receipts, contracts, etc., form the basis of entry. Now this is an accounting reality.

2. ER Design: ER Design refers to the formal blueprint showing use of Entity Relationship (ER) concepts to represent the description of reality.

3. Relational Data Model: Relational Data Model refers to data model through which ER design is transformed into inter – related data tables along with the restrictions in the form of rules that are specified to ensure the consistency and integrity of the stored data.

4. Normalisation: Normalisation refers to the process through which database design is refined so that the duplicate or redundant data is eliminated or reduced.

5. Refinement: As an outcome of the completion of normalization process discussed above, the database design is arrived at. The database design thus reached is the final database design as it does not require any further refinement.


What do you understand by accounting data? Discuss the stages through which it is finally transformed for being presented as information in financial statements.

Data processing involves collection, sorting, relating, interpreting and processing in such a manner that raw data provides meaningful information. The following are the different stages through which it passes before being presented as information in financial statements.

1. Source Documents

2. Data input

3. Manipulation of Data

4. Output of Data



What do you understand by database. How does it differ from DBMS?

In accounting, typically, an organization collects processes and stores the financial and material resources or data. The data of a particular object is collected and stored at one place in a systematic manner. The data thus collected is processed to eliminate duplicate records. The data collected and stored will have entire data of the object, but only a part of the whole data is relevant to a particular user department. The collected and stored data is the database out of which a relevant part of the data can be retrieved by the user department to the extent it is permitted by the data administrator.

DBMS is a collection of programs that help us to create and maintain a database. It is a general purpose software system that facilitates the processes of defining, constructing and manipulating databases for various applications.


What is meant by entity type? How it is different from entity set? Illustrate by giving suitable example from accounting reality.

Entities are the basic units used in modeling classes of concrete or abstract objects. An entity is an object that is of interest to an organization. Two objects are mutually distinguishable and this fact is represented in the entity set by giving them unique identifiers. An entity set is a collection of all entities of a particular entity type. An entity type describes schema or a set of entities that share the same set of attributes.


What do you understand by relationship type? How is it different from relationship instance and relationship set?

An association among entities is called a relationship. The relationship set is used in data modeling to represent an association between entity sets. This association may have certain properties represented by the attributes of the relationship set. A collection of relationships of the same type is called a relationship set. A relationship that involves N entities is called N – ary relationship. A relationship is a binary relationship if the number of entity sets involved in the relationship is two. Enrolment is an example of a binary relationship involving two distinct entity sets like between the student and course. Examination is an example of binary relationship which shows the relation between a student and roll number.


What do you understand by multi-valued attribute? How is it different from complex and composite attribute? Illustrate by giving suitable example.

An attribute with multi value is a multi – valued attributes. The composite and null – valued attributes may be nested (grouped) to constitute complex ones.


What do you understand by the concept of weak entity used in data modelling? Explain the relevance of owner entity type, partial key and identifying relationship in the context of such modelling.

A weak entity is one which does not have an identifier of its own. A weak entity type is identified with respect to its relationship because it cannot be identified without its owner entity. Let us consider a voucher. A voucher may be accompanied by a set of support documents, such as bills, detail of expenses, issued by other parties to the transaction. Such support documents are weak entity type which are used to keep track of support documents attached to each voucher via N- relationship.


What is a participation role? State the circumstances under which the use of role names becomes necessary in description of relationship types.

Each entity type that participates in a relationship type plays a particular role in the relationship. The role name signifies the role that a participating entity of an entity type plays in each relationship instance.


Define foreign key. How is this concept useful in relational data model? Illustrate with suitable example.

When the primary key values of one relation appear in other relations, they are termed foreign keys. Note that foreign keys may have redundant occurrences in a relation, while primary keys may not. For example, C# in Transaction is a foreign key and the key value ‘1’ occurs in two different tuples. This is allowed because a foreign key is only a reference to a tuple in another relation, unlike a primary key value, which must uniquely identify a tuple in the relation.


What is meant by NULL value? What are the reasons that lead to their occurrence in database relations?

Entity integrity constraint requires that primary key value cannot be null because it is used for the identification of the individual tuple in a relation. Null value shows non –identification or duplicity or failure to distinguish such tuples.


Why are duplicate tuples not allowed in a relation?

Each value in a tuple is an indivisible value to imply rational model. This implies that composite and multi-valued attributes are not allowed.


What is the need for database normalisation?

Normalisation refers to the process through which database design is refined so that the duplicate or redundant data is eliminated or reduced.


Discuss the basic concepts of Entity Relationship (ER) Model. Illustrate as to how an ER model is diagrammed.

The entity-relationship (ER) data model is developed out of the exercise of using commercially available DBMS to model application database. Earlier, commercial systems were based on the hierarchical and network approach. The entity-relationship model is a generalization of these models. It allows the representation of explicit constraints as well as relationships. This model of database consists of entities, attributes, identifiers and relationships which are used to express a reality for which database is to be designed. The database structure, employing the ER Model, is usually shown pictorially by using entity – relationship (ER) diagrams. The entities and the relationships between them are shown by using the ER symbols to represent different types of entities, attributes, identifiers and relationships. The symbols, which are used for the purpose, are standardized and are as follows:

An entity is shown as a rectangle

A weak entity is shown as a double lined rectangle

A diamond represents the relationship among a number of entities, which are connected to the diamond by lines.

Identified relationship is shown as a double lined diamond.

The attributes shown as ovals are connected to the entities or relationships by lines.

Key attribute is shown as names enclosed in ovals and attached to their entity type by straight lines.

Multi – valued attributes are shown as double ovals

Derived attributes are shown as dashed line ovals
Diamonds, ovals and rectangles are labeled. The type of relationship existing between the entities is represented by giving the cardinality of the relationship on the line joining the relationship to the entity.


What integrity constraints are specified on database schema? Why is each considered important?

Constraints of relational databases are- Domain: the value of each attribute of a relation must be an indivisible value and must be drawn out of possible values associated with its domain. The value of an attribute, therefore, must conform to the data type associated with the domain.
  Key Constraints: a key is part of a tuple (one or more attributes) that uniquely distinguishes it from other tuples in a given relation. Of course, in the extreme, the entire tuple is the key since each tuple in the relation is guaranteed to be unique. However, we are interested in smaller keys, if they exist, for a number of practical reasons. First, keys will typically be used as links, ie., key values will appear in other relations to represent their associated tuples. Thus, keys should be as small as possible and comprise only non – redundant attributes to avoid unnecessary duplication of data across relations. Second, keys from the basis for constructing indexes to speed up retrieval of tuples from a relation. Small keys will decrease the size of indexes and the time to look up an index.









New Delhi








New Delhi


The customer number (C#) attributes is clearly designed to uniquely identify a customer. Thus, we would not find two or more tuples in the relation having the same customer number and therefore it can serve as a unique key to tuples in the relation.

However, there may be more than one such key in any relation, and these keys may arise from natural attributes of the entity represented (rather than a contrived one, like customer number). Examining again, no two or more tuples have the same value combination of Ccity and Cphone. If we can safely assume that no customer will share a residence and phone number with any other customer, then this combination is one such key. Next, note that Cphone is not alone – there are two tuples with the same Cphone value (telephone numbers in different cities that happen to be the same). And neither is Ccity alone, as we may expect many customers to live in a given city.









New Delhi








New Delhi


C# Key – 1


Ccity & Cphone – Key2



While a relation may have two or more candidate keys, one must be selected and designated as the primary key in the database schema. In the example given above, C# is the obvious choice as a primary key for the reasons stated earlier. When the primary key values of one relation appear in other relations, they are termed foreign keys. Note that foreign keys may have redundant occurrences in a relation, while primary keys may not.

For example, C# in Transaction is a foreign key and the key value ‘1’ occurs in two different tuples. This is allowed because a foreign key is only a reference to a tuple in another relation, unlike a primary key value, which must uniquely identify a tuple in the relation.


Discuss the different types of update operations in relation to the integrity constraints which must be satisfied in a relational database model.

A Relational Database Schema is made up of a number of relational database schemas and also a set of integrity constraints. A relational database is based ion relation scheme consisting of a number of attributes. It is a set of relation states such that every relational database state satisfies the integrity constraints specified on relational database schema. From another point of view, a relation is a subset of the Cartesian product of the domains.

Each tuple in a relation represents an identifiable instance of an object type. But it should also be considered that the set of tuples in the relation are not static but can vary with time. The set of attributes on which the tuples are defined is the invariant. This is called the scheme of the relation or the relation scheme. The relation has two parts – a relation scheme and a time – varying set of tuples.

A Relational Database Schema comprises of –

1. the definition of all domains

2. the definition of all relations, specifying for each

a. its intension and

b. a primary key


However, there is a useful notation for relational schemas commonly adopted to document and communicate database designs free of any specific DDL. It takes the simple form:

<relation name>:<list of attribute names>

Additionally, attributes that are a part of the primary key are underlined. Thus, for the example in Exhibit 1.21 the schema would be written as follows:

Customer       : (C#, C Name, Ccity, Cphone)

Transaction    : (C#, P#, Date, Qnt)

Product          : (P#, Pname, Price)

This notation is useful in clarifying the overall organization of the database but omits some details, particularly the properties of domains. As an example of a more complete definition using a more concrete DDL, we rewrite some of the schema about using Amar’s original notation. The principal components of his notation are annotated alongside.

Database State and Instances: The data in the database at a particular moment is called database state or snapshot. This is also called current set of occurrence or instances.

When a new database is defined, its state is empty. The initial state of database occurs only when the database is first populated or loaded with initial data.


Discuss the steps you would take to transform an ER Model into various relations of Relational Data Model. Give suitable examples.

Database technology refers to a set of techniques used for designing a database. Database design requires use of several techniques of certain concepts at the same time. These concepts consist of reality, data, database, information, DBMS and database system.

Reality: Reality refers to an aspect of the real world. Let us consider an organization. It has different departments and components and also it has a set of an environment in which it exists and operates. Each organization operates within an environment. While operating, the organization interacts, influences and gets influenced by the environment.

Data: Data means meaningful facts related to the resources, such as people, places, objects, entities, events or even concepts. Data can be quantitative and qualitative or financial and non-financial.

Database: Database system is a system where the data required for operation is collected, stored and disseminated under a single administration. The collected and stored data can be used by a number of users. Thus, database has two important properties, ie., it is integrated and it is shared. A database is a shared collection of interrelated data tables, files or structures, which are designed to meet the varied informational needs of an organization. Integrated data implies that distinct data tables have been logically organized to reduce duplicity and for easy data access. Shared property implies that all those who are authorized to use data have access to the relevant data. Accordingly, accounting database is a collection of related accounting data to represent some aspect of an accounting information system. Database is designed, built and populated with data for a specific purpose.


Information: Information refers to information generated in a suitable format, by the processing of data, for easy understanding and, thus, decision-making. In other words, the raw data when processed generates information. For example, transactions (raw data) are recorded in the accounting software, which the software processes to generate information, ie., ledger, trial balance and financial statements.


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