How Raw Data Becomes Usable Information in Research Projects

How Raw Data Becomes Usable Information in Research Projects

From Raw Data to a Research Question

Data can become useable in many area's of life, business, education and research. To answer the question 'How does data become usable information' the answer will be directed to a business question that needs to be answered.

Data in a business or a research project collected for quantitative or qualitative purposes will need framework or structure around it to make it usable. The raw data by itself doesn't make the data usable. We normally collect data to answer a question or a series of questions. Having worked as a Database Administrator for a few years, we are always asked to collect data.

The research instrument is the physical tool to collect the data or could be the method that the raw data is collected. The data could be collected by sensor, questionnaire, or interviews.

Before we create sensor, questionnaire or interview questions to collect the raw data, we need to have the objective, research question or hypothesis we are trying to answer. Before collecting raw data we need want to define the who, what, when and where of the questions we are asking to be sure we are collecting the right raw data to draw conclusions or the answers to our research question or questions from the raw data we collect.

Data become useable if the person, company, research project defines what the reason we are collecting the data for. This is usually done to answer a business question, educate someone or answer a research question.

Research Instruments: A Website Example

An example might be the Amazon.com marketing and advertising team would like to know what you are shopping for so they might recommend other things you might like to buy, which would increase possibility of you buying something while visiting Amazon.com. This would lead to increasing revenue for the company.

So the statement above defines the research problem or a requirement in the business world. Once have the research problem, we need to identify the research instrument(s).

In the computer world when a user visits a website, one example of a research instrument would be the weblogs from the web server that the users is browsing products. The webserver records each page the user was on. This would be one research instrument.

Another research instrument might be a custom program that would be written to collect detailed information on anything the users clicks on while browsing products and other information on the website. This would be great amount of raw data collected and be the second research instrument in our example.

The raw data from the web server logs normally can be collected in one of a few web logging standards. The custom program can be designed to collect specific browsing information for the marketing and advertising team. We now need to make sense of this information. That would be done by defining requirements. The team would have to define objectives, research questions or hypotheses in this case for data that needs to be collected to recommend to a user other products.

How Data Can Be Misused

One persons data can be another ones treasure. Credit cards numbers are misused on a regular basis. We make money, we use credit cards to pay for items. It works pretty well.

Then your credit card falls into the wrong hands. The credit card number can be misused by someone else. I recently had my credit card number stolen. For me the credit card number is used for buying things. This number was misused by someone else without my permission. In fact still wondering how they got the information(my credit card number). They could have stolen it via a card skimming method for example. Card skimming is a sensor put on a card reader to collect a credit card number for misuse. There are people out there taking information such as credit cards, and misusing it for something they should not be doing. So this is an example of taking my good data and turning it into bad data by thieves when they are spending money on my credit card for their pleasure and or monetary gain.

Quantitative Data in Two News Stories

The Article 'Hedge funds bolster quantitative know-how' discusses how hedge funds are using machine learning to collect data and using it for quantitative analysis to help make investment or trading decision in the stock market. The idea of using quantitative data is to lower the risk of investing by collecting quantitative data. The investment manager is collecting data points to influence when to buy and when to sell or when a stock will increase or decrease in value.

The article 'Traders made millions on stocks after hacking press releases' discusses how traders fabricated data to make investment decisions.

The First article 'Hedge funds bolster quantitative know', where the Hedge Fund is using quantitative raw data make investment decision's. The company is making raw data useable for investment decisions.

The second article, 'Traders made millions on stocks after hacking press releases' depicts a method of creating fake press releases or quantitative data to inflate stock prices. Before doing so buying into the stock and then selling it soon after. This is making use of raw data for investment decision for misuse.

Primary and Secondary Sources

Primary research is formulating and testing a hypothesis or collecting the information through observation, or conducting a survey then reporting the results to others in the field.

Secondary research would be reading various reports of previous research then analyzing the results. From that one would formulate a combined opinion the topic to the field. This research is referred to as secondary since it uses reports of previous primary and secondary research

References

Childs, M., & Wigglesworth, R. (2016). Hedge funds bolster quantitative know-how. FT.com.

Hughes, M. A., & Hayhoe, G. F. (2009). A research primer for technical communication: Methods, exemplars, and analyses . Taylor and Francis.

Isidore, C. (2015). Traders made millions on stocks after hacking press releases. CNN Wire Service.

Kumar, R. (2014). Research methodology: A step-by-step guide for beginners . London, United Kingdom: Sage Publications.