# What is Data

Topics: Research, Data, Scientific method Pages: 7 (1888 words) Published: February 7, 2015
Faculty of Social Science
Department of Economics

Course of study: MBA
Course Title: Marketing Research
Course code: MBA 763

Assignment: Secondary Data
Mat Number: 74168
Name: Abiona Timothy Olufemi

What is Data
Data is a collection of facts, such as numbers, words, measurements, observations or even just descriptions of things. 1.Information in raw or unorganized form (such as alphabets, numbers, or symbols) that refer to, or represent, conditions, ideas, or objects. Data is limitless and present everywhere in the universe. See also information and knowledge. 2.Computers: Symbols or signals that are input, stored, and processed by a computer, for output as usable information. Data is a set of values of qualitative or quantitative variables; restated, pieces of data are individual pieces of information. Data is measured, collected and reported, and analyzed, whereupon it can be visualized using graphs or images. Generally and in science, data is a gathered body of facts.

Data, information and knowledge are closely related terms, but each has its own role in relation to the other. Data is collected and analyzed to create information suitable for making decisions,[3] while knowledge is derived from extensive amounts of experience dealing with information on a subject. For example, the height of Mt. Everest is generally considered to be data. This data may be included in a book along with other data on Mt. Everest to describe the mountain in a manner useful for those who wish to make a decision about the best method to climb it. Using an understanding based on experience climbing mountains to advise persons on the way to reach Mt. Everest's peak may be seen as "knowledge".

Types of Data
Data can be qualitative or quantitative.
Qualitative data is descriptive information (it describes something) Quantitative data, is numerical information (numbers).

And Quantitative data can also be Discrete or Continuous: Discrete data can only take certain values (like whole numbers) Continuous data can take any value (within a range)
Put simply: Discrete data is counted, Continuous data is measured

Sources of Data
Researchers need to consider the sources on which to base and confirm their research and findings. They have a choice between primary data and secondary sources and the use of both, which is termed triangulation, or dual methodology. Primary data is the data collected by the researcher themselves, i.e. 1. interview

2. observation
3. action research
4. case studies
5. life histories
6. questionnaires
7. ethnographic research
8. longitudinal studies
When someone refers to "primary data" they are referring to data collected by the researcher himself/herself. This is data that has never been gathered before, whether in a particular way, or at a certain period of time. Researchers tend to gather this type of data when what they want cannot be find from outside sources. You can tailor your data questions and collection to fit the need of your research questions. This can be an extremely costly task and, if associated with a college or institute, requires permission and authorization to collect such data. Issues of consent and confidentiality are of extreme importance. Primary data actually follows behind secondary data because you should use current information and data before collecting more so you can be informed about what has already been discovered on a particular research topic. Secondary sources are data that already exists

1. Previous research
2. Official statistics
3. Mass media products
4. Diaries
5. Letters
6. Government reports
7. Web information
8. Historical data and information
If the time or hassle of collecting your own data is too much, or the data collection has already been done, secondary data may be more appropriate for your research. This type of data typically comes from other studies done by other institutions or organizations. There is no...

Bibliography: 3. P. Beynon-Davies (2002). Information Systems: An introduction to informatics in organisations. Basingstoke, UK: Palgrave Macmillan. ISBN 0-333-96390-3.
4. P. Beynon-Davies (2009). Business information systems. Basingstoke, UK: Palgrave. ISBN 978-0-230-20368-6.
6.  P. Checkland and S. Holwell (1998). Information, Systems, and Information Systems: Making Sense of the Field. Chichester, West Sussex: John Wiley & Sons. pp. 86–89. ISBN 0-471-95820-4.