07292023-Q1 & Q2

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Quantitative Data Collection Instrument

Overview: Using the topic and research question you developed in week 1, you will design a quantitative instrument that could potentially answer your topic/research question if it were to be applied to a quantitative study. Keep in mind, this may take some stretching if you wrote your question leaning quantitatively. The purpose here is not to box you in but to ensure that you have a solid understanding of both methodologies. This assignment functions similar to 3.1 but in a quantitative format. Finally, view the rubric and examples to make sure you understand the expectations of this assignment.

Directions:

You will develop a word document to include:

1. Your research question in the form of a quantitative question (if it was not already).

2. An instrument or protocol (survey, questionaire, archival data, etc) that could be used to answer the quantitative version of your research question.

*Special note for those using archival data, you will describe the process of data retrieval for your archival data.

3. A one paragraph description/justification of how your chosen instrument/protocol is the best choice for answering the quantitative version of your research question. This should include citations from the literature to support justification.

View the rubric: DSRT 837 Rubric Adapted from Doctoral Research Handbook.docx

Week1 Research Question:

Using Data Science Techniques To Enhance Data Security in SMBs

Data science is being embedded into cyber security and data security. It is being used to identify the patterns of past attacks and predict the potential risks within the framework of the system. Machine learning is highly used in analyzing large data sets to find the patterns that spot an attack.

Due to the high licensing cost and contracts, many small and medium-scale businesses use open-source tools and applications. This tends to put these organizations in harm’s way. Due to the low volume of data or fewer users in the organization, the management will choose open-source software tools, which sometimes have fewer security protocols and high exposure to data breaches and security threats.

Research Questions:

· What drives SMBs to choose open-source technologies?

· How safe are these open-source data science technologies?

· What measures can be taken to aid SMBs in using open-source data science tools to protect their data better?

I work with a small insurance firm where various open-source applications are used daily. I want to leverage my experience and access to this situation and try finding answers to the above along with my research. I plan to find the reasons behind the management’s decisions and what factors drive technical teams to choose particular open-source technologies. I will research more on their pitfalls and successful implementations.

DSRT 837 Rubric (Adapted from Doctoral Research Handbook)

Criterion	4 (Expert)	3 (Proficient)	2 (Fair)	1 (Poor)
I. Critical and reflective thinking capable of facilitating institutional, informational technology, or business related problem-solving or school/ college improvement	Critically analyzed the topic. Discussion of the topic was extensive and anchored in fact and reason. Information about significant aspects of the topic were analyzed from the perspective of key related concepts. Meaning of the analysis was summarized.	Critically analyzed the topic. Discussion of the topic was anchored in fact and reason. Information about significant aspects of the topic were analyzed from the perspective of key related concepts. Either the analysis or summary lacked some level of detail.	Somewhat critically analyzed the topic. Discussion of the topic was minimally anchored in fact and reason. Information about significant aspects of the topic were somewhat analyzed from the perspective of key related concepts. Analysis and summary included but lacks a significant level of analysis and discussion.	Minimally discussed the topic without supporting facts and reasons. Poor organization of the information and limited level of detail.
II. Consideration for the impact of leadership, information technology, or business on institutional constituents.	Demonstrates an extensive understanding of the topic’s relationship to leadership, information technology, or business.	Demonstrates a good understanding of the topic’s relationship to leadership, information technology, or business.	Demonstrates a fair understanding of the topic’s relationship to leadership, information technology, or business.	Demonstrates a minimal understanding of the topic’s relationship to leadership, information technology, or business.
III. Effective analytical and communication skills	Demonstrates a professional level of skills associated with formatting, grammar, spelling, syntax, and use of numbers.	Demonstrates acceptable skills associated with formatting, grammar, spelling, syntax, and use of numbers.	Needs minor improvement in skills associated with formatting, grammar, spelling, syntax, and use of numbers.	Needs significant improvement in skills associated formatting, grammar, spelling, syntax, and use of numbers.
IV. Knowledge of genres, paradigms, theories, literature or trends in business, criminal justice, education, English, health sciences, history, information technology, math, nursing, psychology, religion, or student personnel services.	Subject is identified, realistic, and grounded in a recognized genre, paradigm, theory, literature, or trend.	Subject is identified and is realistic, but it lacks grounding in a recognized genre, paradigm, theory, literature, or trend.	Subject is identified but is not realistic or grounded in a recognized genre, paradigm, theory, literature, or trend.	Subject area is not established.
V. Required Components of the assignment as listed in the assignment directions.	All required parts of the assignment as listed in the assignment directions are included.	Minor information is missing from the required components of the assignment as listed in the assignment directions.	Significant information is missing from the required components of the assignment as listed in the assignment directions.	The assignment lacks the detail needed to meet the requirements for the components of the assignment as listed in the assignment directions.