This is the information that comes from within the organisation. Examples include internal financial reports, such as the level of sales being made in different markets or the cost of running the transport fleet of lorries or market analysis which is an internally produced report into how national and international markets are faring.
This is information that comes from outside the organisation. Examples include supplier price lists which are lists of products and the price charged for them and financial reports from a third party which would have the same focus as internally produced reports but would be produced by someone outside the organisation.
This is the data that you collect rather than buy from a third party. Examples include reports that have been created by employees such as the result of a period of observation at a road junction counting vehicles by type.
This is the data that has been collected by others outside the organisation. Examples include survey results that have been collected for a different organisation (and usually for a different purpose) or factual information provided by a third party such as prices charged by another organisation.
Qualitative data is descriptive data that cannot be measured but can be recorded. For example:
- names and addresses
- people's favourite flower
- the texture of a wall
- people's opinion on the current computer system (shocking, totally shocking!)
Quantitative data is measurable and is usually in numeric form because it records a quantity. For example:
- the number of people who work on a project
- the time it takes to complete an activity
- the size of a room
- the number of records stored in a database.
Qualitative data and quantitative data
The fundamental difference between these two terms is that quantitative data is data that has been gathered by some form of measurement, while qualitative data that describes. An example of quantitative data would be the number of staff working in an organisation whereas qualitative data would be the opinion about a new initiative.
Complete this table (Examples of qualitative and quantitative data)
|The colour of a car|
|The number of blue cars sold last year|
|Results of a questionnaire about the age of students attending a college|
|Results of a questionnaire gathering suggestions for a new design of Eco-home|
|The height of a building|
|Do people like chocolate?|
|How many people like chocolate?|
Different data sources provide different types of data that suit different needs. For example, secondary data can be a relatively cheap way of gathering non-specific information. If you need to know how many people lived in a certain city, primary research would involve many hours of detailed investigation so you could us the results of someone else's research which will already exist.
However, secondary data is probably of limited use for really focused research. Imagine a shampoo manufacturer wants to gather information about how many people would buy its new apple-scented shampoo. Secondary data may exist for the sales figures for a rival's product but would that be sufficiently accurate to act as a gauge for the success of the new product? It may be a god starting point but it would not be a wholly reliable source of data on which to base a marketing campaign and production policy.
Data flow diagrams (DFDs)
Data flow diagrams model how data flows through a system. An example system could be used to create weekly wage slips so that wages can be paid.
A DFD shows how data moves through a system - from where it comes, what is input, what happens to this data, what is output or how it is output and where is is stored within the system.
These are the main symbols used in a DFD. Entities (source/sink) are the external people or systems, from where the data is input or to where the data is output. Processes describe the actions to be performed on the data and the data stores are the data storage within the system; for example a database table, a text file or a csv file. The data flows are shown as arrows moving from one element to another. A DFD is unlikely to explain how the processes take place or how calculations for example are performed.
There are many industry-standard DFD symbols - all are acceptable. In school we will use Visio's version of Gane and Sarson symbols.
External entities are sources of data that is input into the system and those to whom data that is output is sent and who are also external to the system itself (outside the system boundary). In a school report system the external entities would include the teaching staff (inputs) and parents (outputs). A database that held the collated reports for an individual student would be an internal entity as it is within the system boundary.
These are the ways in which the data in the system is collated. In the example of a school report system there would be one central process that would collate the scores and comments made by the individual teachers into one overall report for each child.
Data stores represent any real world store of data held in the system. This could be in a database but could also be in a filing cabinet or an in-box on someone's desk.
These are the flows of data between the entities and processes.
Connectivity rules for drawing level 1 DFDs
Drawing DFDs can be a complicated task. However there are some rules that make the process a little easier.
At least one output or input for each external entity. This may seem obvious, but each external entity is either submitting or receiving data; if not why are they in the DFD?
Data flows only in a single direction. This causes some confusion. Data flow (indicated by an arrow) can only flow in a single direction with a label describing the data flowing on the arrow. If data is returned along the same path then an second arrow identifying the new flow is used rather than a double arrow.
Every data flow is labeled. Each data flow must have an arrow showing the direction of flow of the data as well as a label that identifies the data that is being transferred.
Every data flow connects to at least one process. This is another possible source of confusion. However when considered logically, each data flow is either going to a data store following processing or coming from a data store ready to be processed.
There must be at least one input flow and /or at least one output flow for each process. In order for the system to work, data must come from somewhere at the start of the process and go somewhere at the end. In theory then, a process should have at least on input flow and at least one output flow, however, the source or destination of the data being processed may be another part of the system. Thus it may be the other system where further processing takes place.
When producing DFDs it can help to write a list of what happens in a system for example:
- the employee enters the hours they have worked this week
- the system gets their hourly rate from the staff database
- the systems works out how much they should be paid
- the system sends this amount to the accounts database
- the system produces a payslip
- the payslip is sent to administrator
- the administrator sends the payslip to the current employee.
Impacts affecting the flow of information in information systems
Data flow systems rearely completely fail to transfer data. Far more likely os that the flow of data is delayed. If the system is computersied, even parttial system failure could result in a delay while thye technology is restored or improved. Human error could result in data being lost or misfiled, so that it would need to be found. or a result in data being processed in the wrong order of importance (such as somsone working on their own favourite project rather than the one that needs doing).
Breakdowns in working relationships can result in delays, especially where the means of transfer of data involves two people meeting. However there could be a delay becuae someone put off doing a task simply because they do not like the person waiting for the outcome.
- 1. An organisation has internal or external information available to answer a query.
- a) describe one reason why the orghanisation may choose to use the internal information.
- b) describe one reason why the orghanisation may choose to use the external information.
- 2. Compare the terms qualitative and quantitative data.
- 3. Identify three external entities for a train booking system.
- 4. Identify two data flows for an electricity billing system.
- 5. Desribe one characteristoc of a smoothly flowing data management system.