Bank Account Management Data Flow

Data Flow Model – Bank Account Management System

In the following, we are presenting a data flow model that describes an accounts management system for a bank. This data flow diagram consists of the following entities,

Click to Enlarge

 Processes
1. Reconcile account balance
2. Deposit funds into an account
3. Pay a bill
4. Withdraw funds from an account

External agents
1. Bank
2. Creditor
3. Employer
4. Other income sources

Data stores
1. Monthly Account statement
2. Bank accounts
3. Account transactions

Description:
First we shall discuss ‘withdraw funds from an account’ process. In this process, information about the  accounts and account transactions is retrieved (from the data stores) and bank releases the funds. After this,  it sends this information to ‘reconcile account balance’ process which prepares a monthly account statement.  In this statement, information regarding bank accounts and account transactions are described.  Next is the ‘pay a bill’ process through which a creditor pays his dues and the corresponding accounts are  updated against the cash transaction. A receipt is issued back to the creditor. The fourth process is ‘deposits  funds in an account’ in which an employer deposits salaries of his employees and the salary information is  deposited in the corresponding bank accounts of the employees. Similarly, income received through other income sources is also received and deposited in the corresponding bank accounts.

The next post will also concern to data flow having some Data Flow Modeling techniques.

Data Flow Versus Flow Charts

DFD versus Flow Charts

Flow charts are usually used to describe flow of control in a system. It describes control flow in an algorithm.  Flow charts are quite detailed. Whereas DFD does not captures control flow information, it just  shows the flow of the data in a system. Flow charts show the sequential activities of an algorithm. So,  decisions are made, loops or iterations are described. On the other hand, DFD does not show the sequential  activities. It just displays the business flow (without sequence among activities). As if you visit an  organization, business activities are being performed in parallel. Therefore, DFD does not contain control or  sequential activities just data transition is captured.

DFD	DFD Flow Chart
-Processes on a data flow can operate in parallel. -Looping and branching are typically not shown. -Each process path may have a very different timing.	-Processes on flowcharts are sequential. -Show the sequence of steps as an algorithm and hence looping and branching are part of flowcharts.

The Next will be the Example of Data Flow Model of Bank Account Management System.

Data Flow Model

Data Flow Model

• Captures the flow of data in a system.
• It helps in developing an understanding of system’s functionality.
• What are the different sources of data, what different transformations take place on data and what are  final outputs generated by these transformations.
• It describes data origination, transformations and consumption in a system.
• Information is organized and disseminated at different levels of abstraction. Thus this technique  becomes a conduit for top down system analysis and requirements modeling.

The Notation
There are several notations of the data flow diagrams. In the following, four different shapes are explained.

Process

• What are different processes or work to be done in the system.
• Transforms of data. 

Process

External AgentExternal systems which are outside the boundary of this system. These are represented using the squares

External Agent

 Data Store

• Where data is being stored for later retrieval.
• Provides input to the process
• Outputs of the processes may be going into these data stores.

Data Store

 Data Flow

• Where the data is flowing.
• Represents the movement of the data in a data flow diagram.

Data Flow

Information in Tabular Form

Arranging information in tabular form

Sometimes it is better and more convenient to arrange information in a tabular form. This makes it easier for  the reader to understand and comprehend the information and hence designing, coding, and testing become  less challenging. As an example, let us look at the following definitions used for identifying different data  functions in the function point analysis taken from International Function Point User’s Group (IFPUG)  Counting Practices Manual (CPM 4.1).

External Inputs
An external input (EI) is an elementary process that processes data or control information that comes from  outside the application boundary. The primary intent of an EI is to maintain one or more ILFs and/or to alter  the behavior of the system.

External Outputs
An external output (EO) is an elementary process that sends data or control information outside the  application boundary. The primary intent of an external output is to present information to a user through  processing logic other than, or in addition to, the retrieval of data or control information. The processing logic  must contain at least one mathematical formula or calculation, or create derived data. An external  output may also maintain one or more ILFs and/or alter the behavior of the system.

External Inquiry
An external inquiry (EQ) is an elementary process that sends data or control information outside the  application boundary. The primary intent of an external inquiry is to present information to a user through the  retrieval of data or control information from an ILF or EIF. The processing logic contains no mathematical  formulas or calculations, and creates no derived data. No ILF is maintained during the processing, nor is the  behavior of the system altered.

It is difficult to understand these definitions and one has to read them a number of times to understand what is  the difference between EI, EO, and EQ and in which case a function would be classified as EI, EO, or  EQ.

Now the same information is presented in the tabular form as follows:

Information in Tabular Form - Click to Enlarge

PI – Primary intent; M – may be; N/A – not allowed.

This table simply says that a function can alter the behaviour of the system, it can maintain one or more ILFs,  and/or it can present information to the user. The next step is to determine whether it is EI, EO, or EQ. For  that we have to determine what is the primary intent (PI) of the function and in addition to this primary intent,  what else does it do. Identification of EQ is simple - in this case the only thing a function does is present
information to the user, which is also it’s primary intent. If it alters the behaviour of the system or maintains  and ILF then it can either be an EI or and EO but not an EQ. On the other hand if the primary intent of the  function is to present information to the user but at the same time it also performs any of the first two  operations, it is an EO. Finally, if the primary intent of the function is either to alter the behaviour of the  system of maintain one or more ILFs, then it is an EI.

Hence by putting and organizing the information in the form of a table, we have not only made it simple to  understand the definition but also given an holistic picture which was not easily visible otherwise. Let us look  at another example. This time the information is taken from the Income Tax Ordinance of Pakistan 2001.  Consider the following statement that describes the income tax rates applicable to people with different brackets:

If the taxable income is less than Rs. 60,000, there will be no income tax. If the income exceeds Rs. 60,000   but is less than Rs. 150,000 then income tax will be charged at the rate of 7.5% for income exceeding Rs.   60,000. If the income exceeds Rs. 150,000 but does not exceed Rs. 300,000 then the income tax will be  computed at 12.5% of the amount exceeding Rs. 150,000 plus Rs. 6,750. If the income exceeds Rs.  300,000 but does not exceed Rs. 400,000 then the income tax will be computed at 20% of the amount  exceeding Rs. 300,000 plus Rs. 25,500. If the income exceeds Rs. 400,000 by does not exceed Rs.  700,000 then the income tax will be computed at 25% of the amount exceeding Rs. 400,000 plus Rs.  45,500. If the income exceeds Rs. 700,000 then the income tax will be computed at 35% of the amount  exceeding Rs. 700,000 plus Rs. 120,500.

The same information can be organized in the form of a table, making it more readable and easier to use.

Income	Tax
Less than Rs. 60,000	0%
Between Rs. 60,000 and Rs. 150,000	7.5% of (Income - 60,000)
Between Rs. 150,000 and Rs. 300,000	12.5% of (Income - 150,000) + 6,750
Between Rs. 300,000 and Rs. 400,000	20% of (Income - 300,000) + 25,500
Between Rs. 400,000 and Rs. 700,000	25% of (Income - 400,000) + 45,500
Greater than Rs. 700,000	35% of (Income - 700,000) + 120,500

Once the information has been organized in the tabular form, in many cases it can be simply stored and  mapped onto an array or a database table and the programming of this kind of a rule is simply reduced to a  table or dictionary lookup. This reduces the complexity of the domain and hence reduces the over all effort  for designing, coding, testing, and maintaining the system.

Our next post will be about Data Flow Model.