| Course | DAM-7020 Predictive Analytics for Business Intelligence |
|---|---|
| Module | Module 2 |
| Paper type | Written assignment: trends in business analytics |
| Length | About 535 words, 4 pages |
| Format | APA 7 student paper |
| School | Thomas Edison State University |
| Program | MBA in Data Analytics |
| Updated | October 2026 |
Free sample paper for DAM 7020 Module 2
Four Trends and One Chain: What Changes in Business Analytics Mean for a Tire and Service Business
Student Name
MBA in Data Analytics, Thomas Edison State University
DAM-7020: Predictive Analytics for Business Intelligence
Mentor Name
Month Day, Year
Four Trends and One Chain: What Changes in Business Analytics Mean for a Tire and Service Business
Why Trends Matter Here
Our chain will spend about $60,000 and much of my time on its first predictive project. Trends shape what that money should buy and what skills the chain needs. Not every trend matters to a forty-store service business, so the question is which ones do.
Trend 1: Data-Driven Decisions Are Spreading
Brynjolfsson and McElheran (2016) used U.S. Census surveys of factories and found that the share of plants deciding by data roughly tripled from 2005 to 2010, with the adopters producing more. The lesson for us is that competitors, including national tire chains, are already using data to stock and staff. Standing still means falling behind.
Trend 2: Analytics as a Capability, Not a Tool
Mikalef et al. (2019) surveyed firms and found that big data analytics capabilities, combining data, technology, skills and an organizational culture that uses data, supported innovation through dynamic capabilities, the ability to sense and respond to change, especially in uncertain environments. Buying software is not enough; the chain needs managers who use forecasts and a habit of checking them.
Trend 3: Cloud Platforms and Automated Modeling
Cloud services let small firms run analyses without servers, and automated machine learning tools can fit and compare many models quickly. For us, the cloud is useful: we can store sales and service history centrally. Automated modeling is less urgent; our first forecasts can use well-understood methods that store managers can be shown, and automation can follow once we know what accuracy we need.
Trend 4: Two Cultures of Modeling
Breiman (2001) split statisticians into two camps: those who posit a model of how the data arose and estimate it to explain, and those who treat the process as a black box and judge methods only by how well they predict. He argued the second, algorithmic culture had been neglected by statisticians despite its success. Business analytics has moved strongly toward prediction. For our chain, both matter: prediction for ordering tires and explanation for managers who want to know why demand rises, such as cold snaps or gas price drops.
| Trend | Relevance to our chain | Action |
|---|---|---|
| Spread of data-driven decisions | High: competitors already forecast | Start the forecasting pilot this quarter |
| Analytics as a capability | High: skills and habits are the gap | Train store managers to read and question forecasts |
| Cloud and automated modeling | Moderate: cloud now, automation later | Move history to cloud storage; delay automated tools |
| Two cultures of modeling | High: need both accuracy and explanation | Compare an interpretable model with a more flexible one |
Preparing for the Midterm and Final
The midterm will gather at least two public data sets that may drive demand, such as vehicle miles traveled and gasoline prices, and the final will build and interpret a forecasting model in R. This review sets the frame: the goal is accurate predictions that managers will trust and use.
Conclusion
Of four trends, three matter now for our chain: data-driven competition, analytics as a capability and the need to balance prediction with explanation. Cloud storage helps immediately, while automated modeling can wait. The forecasting pilot should be built with those priorities.
References
Breiman, L. (2001). Statistical modeling: The two cultures. Statistical Science, 16(3), 199-231. https://doi.org/10.1214/ss/1009213726
Brynjolfsson, E., & McElheran, K. (2016). The rapid adoption of data-driven decision-making. American Economic Review, 106(5), 133-139. https://doi.org/10.1257/aer.p20161016
Mikalef, P., Boura, M., Lekakos, G., & Krogstie, J. (2019). Big data analytics capabilities and innovation: The mediating role of dynamic capabilities and moderating effect of the environment. British Journal of Management, 30(2), 272-298. https://doi.org/10.1111/1467-8551.12343
DAM 7020 Module 2 instructions, in plain terms
DAM-7020 has one written assignment, worth 10 percent, designed to help you prepare for the midterm and final papers; this page places it with Module 2, Trends in Business Analytics. Expect to review current developments in business analytics from research and the course text, judge which matter for a specific organization and explain how they will shape your later work. Pick three or four trends with evidence behind them, tie each to a spending or design decision and close by naming the data the midterm and final will use. Support each trend with a scholarly source rather than a vendor report.
How this DAM 7020 Module 2 example is built
The paper begins with the stakes: a first predictive project and a budget. Four trends are reviewed in turn, each with a source: Brynjolfsson and McElheran on the spread of data-driven decisions, Mikalef and colleagues on analytics as a capability, cloud and automated tools, and Breiman's two cultures of modeling. Each is judged for relevance to the chain. A margin note explains why the review stays tied to the first project. A four-row table summarizes relevance and action, and a short section sets up the midterm's data sets and the final's R model. The conclusion names the three trends that matter now. The paper ends by naming the data and model the later papers will use. Cloud storage is adopted now while automated modeling waits.
Reading the DAM 7020 Module 2 grading rubric
Marks follow trends backed by research, sound judgment about what fits the organization, a clear bridge to the midterm and final, and APA form. Papers that support each trend with a scholarly source and decide what it means in practice show more than papers that list buzzwords. Distinguishing what to adopt now from what to delay shows managerial judgment. Setting up the midterm and final shows planning, which is the assignment's stated purpose. Mentors also look for a clear bridge from the trends to the data and model the student will build next. Deciding what to adopt now and what to delay shows judgment about timing. Clear priorities help.
DAM 7020 Module 2 help: mistakes that cost marks
Students lose points by listing many trends from blogs without evidence, by recommending every new technology or by forgetting that this assignment prepares for the midterm and final. Choose three or four trends with research behind them, judge each for your organization, decide what to do now and later, and explain how the trends shape the data and model you will use next. A free first draft of your DAM-7020 written assignment can be shaped to your organization. End by naming the data sets and the model you plan to use in the midterm and final. Separate trends that matter now from those to watch later, and say why.
Write yours, or have the desk draft it
This paper is an original model document written by our desk, not a submitted student paper and not an official Thomas Edison State University document. Read it for the moves, then write your own to the instructions in your classroom. If you want one built to your exact prompt and rubric, the first custom sample is free and arrives in 24 to 48 hours.
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DAM 7020 Module 2 questions, answered
Where can I find a free DAM 7020 Module 2 sample paper?
The written assignment above judges four business analytics trends for a tire and auto service chain.
What are Breiman's two cultures of statistical modeling?
A data modeling culture that assumes a model to explain relationships and an algorithmic culture that judges methods by predictive accuracy.
Is analytics a technology or a capability?
Research such as Mikalef and colleagues' treats it as a capability combining data, technology, skills and culture.
How fast did data-driven decision making spread?
Brynjolfsson and McElheran found it nearly tripled among U.S. manufacturing plants between 2005 and 2010.
How many written assignments does DAM-7020 have?
One written assignment, worth 10 percent, designed to prepare students for the midterm and final papers.