LB management

Part 1, reply to A and B with 150 words a piece


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Marco Russo and Alberto Ferrari are two non-scholarly Business Intelligence experts.The run a site called SQLBI and have published several books, articles, and training material relative to Business Intelligence.They are keynote speakers at Microsoft Ignite and several other major conferences.No, they do not speak at IEEE conferences, that I can see but that does not diminish their role within the BI (Business Intelligence) community.

SQLBI publishes several articles relative to data modeling, DAX, Power BI, SSAS and tabular modeling.Quite honestly, I have yet to find another scholarly approved resource that is as valuable as most articles provided on SQLBI.Their audience is the novice to expert practitioner.They cover the theory of the application and then the application of the product within the context of the post.For example, their article Bidirectional relationships and ambiguity in DAX (SQLBI, 2019) explains how to create a bidirectional filter within a report.The amount of detail provided, and the illustrative methods used are outstanding.As a practitioner, these types of articles are infinitely more helpful that say a study on the Bidirectional relationship between diabetes and acute pancreatic(Lee, Huang, Hsu, & Su, 2016)

I understand that part of the assignment is to compare a scholarly publication to a non-scholarly publication, but the reality is, with the current availability of the CTU library, there is no study available on the bidirectional methodology with in the database modeling realm from a strictly functional perspective.

The audience for the SQLBI publication is the technician whereas the (Lee, Huang, Hsu, & Su, 2016) is intended for the academic.One proposes a solution to a problem, and one theorizes a solution to a perceived problem.The SQLBI site contains a wealth of knowledge for the practitioner to gain a deeper understanding of the fundamentals of the architecture and informs the reader on the paths to leverage these resources.Unfortunately, most scholarly articles do not take this tone.


The Journal of Big Data is owned by SpringerOpen, which owns over two hundred peer-reviewed, open access journals.SpringerOpen includes journals with subjects from economics to engineering and even social sciences.The Journal of Big Data focuses on big data analytics, methodologies, data visualization, and architecture. I selected, “Mining aspects of customer’s review on the social network,” published in 2019 as an example of a good practitioner article.The article is twenty-one pages long and reviews the different methods available to extract product characteristics, the related sentiment from the reviewer, and a programmer assigned weight to characterize which product characteristics are more important than others (Ngoc, Thu, & Nguyen).The article gives clear examples that could be used for learning how to apply the different methods, graphs for visualization of the results, and the mathematical formulas used by the different methods.The authors include thirty-five references.The article is a good learning article and longer than expected for a practitioner article.This article could be used by a big data dissertation student to learn how to use the different text mining tools mentioned.

For an example of a poor practitioner article, I choose “10 Big Data Trends to Watch in 2019” by the Alex Woodie (2019).The article is roughly five-pages long and discusses ten trends in big data.The articles first trend is entitled “Data Management Is Still Hard,” seeks to point out that the combined ETL and analytic skills needed to extract information from big data environments are hard to find.The second and third trends include the continued increases in data silos and the increase in streaming data. Remaining trends mention the increases in cloud computing, internet-enabled devices, and the increase in artificial intelligence.This article reads like a newspaper article and contains no in-depth review of any trend.The description of each trend is extremely short and reads like an introductory paragraph to what the technology in the trend does.The trends selected are indeed trends in big data.However, for a venue that focuses on data analytics and computing, I would expect anyone reading the article to already know about the majority of those trends.A good practitioner article should probably be focused on a research topic, methodology, or include an in-depth review of a technology.The article should include more statistics and citations.This article is of little to no use to anyone searching for dissertation materials.

Part 2, replay to A and B with 150 words a piece


A dissertation varies from a scholarly article significantly in structure, content and the purpose of writing. Initially, it is affiliated with an academic body and require an approval process before recognizing its validity and recognition. Additionally, it covers a specific topic which may require a significant period to finish, with a purpose to contribute to knowledge, and may lead to further future work. Alternatively, a scholar article may cover many subjects (LAURA, 2017), and can be written swiftly for the purpose of publishing in a reputed journal.

For a modest evaluation of a dissertation, and without underestimating the value and the work accomplished, the below-mentioned topic will be demonstrated as an example. The topic entitled ‘Exploring the big data and machine learning framing concepts for a predictive classification model’ is writing by Jasson Josue Hidalgo in 2018 at Colorado Technical University and can be located under the following link:

Big Data: Hidalgo, J. J. (2018). Exploring the big data and machine learning framing concepts for a predictive classification model (Order No. 10788425). Available from ProQuest Dissertations & Theses Global. (2038464389). Retrieved from . ProQuest Dissertation and Theses Global

After the abstract, dedication and the acknowledgment, the table of contents demonstrate an organized presentation of the content within five chapters along with the conclusion, followed by the references and appendices.

The abstract provides an entire brief of the dissertation within a single page, which gives the reader a clear idea of the overall content and what to expect upon reading the whole document.The first chapter introduces an overview and background of the main topic, followed by the trio of the problem, purpose, research question, and conceptual framework — the primary purpose of the first chapter to offer an overview of the study. Chapter two covers the literature review to investigate the latest updates of the topic and identifying the gap for further research.

The next consecutive two chapters focus on research methods and design. The third chapter states the research method and the approach conducted for data collection and the researched population. Driven by the nature of the topic, the research method adopts the qualitative approach, followed by presenting and analyzing the gathered data. The fourth chapters examine the participants surveyed and analyze the characteristics of the population as demonstrated in graphs and tables. Additionally, it investigates the output produced from the gathered data, supported by explanations and justifications for each question. Chapter five states the findings and the conclusions, emphasizing on the added contribution to the body of knowledge findings gathered from the participants.

The dissertation is well structured and demonstrate a scholarly academic document, with emphasis on the literature, the research methods and findings, and the concluded added contribution. To guarantee concise coverage, the definition of terms offers a further understanding of the technical terminologies, allowing the literature review to focus on the main points. Additionally, the extensive coverage of references and citations supported its comprehensiveness, providing understanding to the researched topic.


(Pouria, 2015)’s dissertation on the performance evaluation of big data systems is and excellent publication.It focuses on architecture, single, and multi-client tests.This provides a strong foundational basis for the dissertation.In addition, the type of analysis such as lookup, insert, and update provide both a technical overview as well as a functional overview of the performance benchmarking of the big data system.Queries are provided for context and cloud-based systems are analyzed as well.Overall, this is a very thorough dissertation on how performance impacts the nature of big data.

(Pouria, 2015)’s chapters are Intro, Performance Evaluation of Key Value Stores, Performance Evaluation of Big Data Management System Functionality, Performance Evaluation of Big Data Analytics Platforms, and Conclusions.

The dissertation is very much a quantitative work.The amount of quantitative methods invested into a singular document is impressive and provides context to the purpose of the research.The dissertation can be found at

The dissertation takes into account the specific details such as the key values of the data and analyzes the performance in handling those keys.This is a great deal of value to a potential researcher as the market moves to a NoSQL or denormalized state. (Pouria, 2015) proves that which good design, a relational database can provide as much performance value as an unstructured database. (Pouria, 2015) covers the difference between the OLTP and OLAP and where those converge such as real-time data analysis.

Overall, I enjoyed reading this dissertation.I believe I have been too focused on the statistical and language aspect of the big data enterprise. (Pouria, 2015) provides a context for a research paper that is not focused on neural networks, R, or Python, yet is still able to produce a work that contributes to the body of knowledge in a meaningful way.

Part 3, reply to A and B with 150 words a piece.


I feel the most compelling topics were the SMART model, our growing edge, and discovering how to write an annotated bibliography. The SMRT model, although similar to what I typically have done in the ARMY, really places emphasis on not just the goal, but also achievable steps to get to your desired end state. I thought this was thought provoking and also instructive on how to manage smaller steps that are far more reachable so as to discourage quitting or feeling overwhelmed. I learned a lot during the growing edge process, a new term to me. This was interesting to learn how we can find out what our growing edge and in a way can also play into the SMART model design to determine what we need our growing edge to be. I really learned a lot in creating an annotated bibliography on my topic of choice, which it was helpful to already have an idea on what I presume my dissertation to be. Joyner, Rouse, and Glatthorn (2018) really did a great job in laying out how to successfully create an annotated bibliography. They discussed organizing, retrieving related abstracts, evaluating results, checking prior works such as dissertations, using primary sources, and creating a comprehensive critique of the literature. Using their method of locating, retrieving, and ensuring these resources were scholarly really helped me during my journey of beginning to become an expert in my chose field.

While participating in discussion I got to learn what my peers were researching and harness ideas from them in their journey. I also received feedback on several of my discussion boards that proved to give great insight to perhaps something I may have overlooked or an additional avenue that may have proven to be fruitful for my collegiate endeavor. I was able to read different perspectives on the things I was also answering and see differing points of view. I appreciate having this interaction with my cohort as we are not in a typical classroom setting where we can garner instant feedback, this is about as close to it as we can get. Unfortunately we were only able to have the one-hour session per week but that is the nature of the beast when we are all careerist and cannot dedicate our every hour to school as we have jobs to carry on.

I liked the class the way it was and I certainly appreciated bringing in the librarians to give blocks of instruction on things outside this particular curriculum such as Grammarly and the doctoral library. I think most of us appreciated the instruction on Endnote as we were incredibly new to it and it was very overwhelming. I always had a quick feedback from Dr. Cone and I appreciate his patience with all of us as we are beginning this journey.


On a personal perspective, Doctoral Research is entirely a new area, and each topic offers an additional learning process and accumulated knowledge. In an attempt to select most three interest topics with significant impact on a personal level, the literature review, the research problem, and the research method are the central area.

A literature review is considered an essential section of the dissertation due to the knowledge and understanding it offers, with the emphasizes on the credibility of the researcher (The Writing Center, n.d.). The primary purpose of the literature review is to provide the current trend and the latest of the topic. It is essential to investigate the most recent and rely on sources with credibility to offer accurate and unbiased findings.Conducting comprehensive critique, guarantees boarder overview and coverage and allow identifying the research gap. By selecting relevant articles gathering and performing analysis ( Joyner, Rouse, & Glatthorn, 2018 ), shows gaining awareness and learning to the topic. The participation in discussion rooms with colleagues has abroad my perspectives to more extensive journal resources and marginally motivate learning new methods. The process of a full scan to gathering and filtering to allocate relevant articles, is implemented by Vasunilashorn, Steinman, Liebig, & Pynoos, 2012) in a three steps plans to find the precise sources . Finding efficient scholar academic articles is a common goal among colleagues, and personally learned significantly from shared experiences in the discussion room.

The next topic is the research problem which is a challenge and demand extensive research and iterative process to allocate the gap within the literature review. The contribution of relatively different opinions and research mechanism of colleagues offers a comprehensive approach to find relevant topics. The main point personally learned from the discussion room is how to investigate related issues which may have a substantial impact on the dissertation topic. The critical is to maintain a focused and reasonable scope and to eliminate any dichotomies content which may lead to generalization and multiple perspectives (Sacred Heart University Library, n.d.).

The third topic is the research method and how to choose whether a qualitative or quantitative method as per the dissertation subject. Having colleagues with a variety of topic orientations across different domains dictates the research method of the dissertation subject . Regardless, of my personal dissertation orientation, it is crucial to learn other available techniques even if not practiced or implemented in my use case. In many circumstances, both can be applied and defined as the triangulation method ( Denzin, 2017).

During the course, questions are addressed frequently, and many have been answered already. However; there is an expectation of further questions in the future and would be looking forward to collaboratively work, learn, and share knowledge with my colleagues. The diversity of experiences gained through the journey of each one of us, enrich the dialogues conducted and elevate the awareness among us.