MIS 690 All Week Assignments GCU

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MIS 690 All Week Assignments GCU

MIS 690 Topic 1 CLC – Business Problem Statement

This is a Collaborative Learning Community (CLC) assignment.

For this assignment, you will use the “Business Problem Statement” template to organize your problem statement. This will help you identify the business problem you will eventually address using analytics. The business problem statement will be an integral component of the remaining activities in this course. Additionally, you will need to complete the relevant components on the “Capstone Project Thesis Template.”

Complete the “Business Problem Statement.”  Ensure that there are accessible data available to address your business problem. You will need to provide your dataset as a part of the Topic 3 assignment. If data are used from your company, ensure that proprietary concerns are addressed or approvals to use the data are obtained. If company data are being used and if there are concerns of proprietary issues, you can change your dataset accordingly.

You are required to include at least three scholarly sources.

Once you have completed the “Business Problem Statement” template, utilize the information to complete the relevant components in the Business Problem Identification section of the “Capstone Project Thesis Template.”

Submit both the “Business Problem Statement” template and the updated “Capstone Project Thesis Template.”

Prepare this assignment according to the guidelines found in the APA Style Guide, located in the Student Success Center. An abstract is not required.

This assignment uses a rubric. Please review the rubric prior to beginning the assignment to become familiar with the expectations for successful completion.

You are required to submit this assignment to LopesWrite. Refer to the LopesWrite Technical Support articles for assistance.

 

MIS 690 Topic 1 CLC – Analytics Problem Statement

This is a Collaborative Learning Community (CLC) assignment.

For this assignment, you will use the “Analytics Problem Statement” template to organize your problem statement. This will help you identify the analytical problem that you will eventually address using analytics. The analytics problem statement will be an integral component of the remaining activities in this course. Additionally, you will need to complete the relevant components on the “Capstone Project Thesis Template.”

Complete the “Analytics Problem Statement” template. Ensure that there are accessible data available to address your business problem. You will need to provide your dataset as a part of the Topic 3 assignment. If using data from your company, ensure that proprietary concerns are addressed or approvals to use the data are obtained. If there are concerns about proprietary issues related to using company data, you can change your dataset accordingly.

You are required to include at least three scholarly sources.

Once you have completed the “Analytics Problem Statement” template, utilize the information to complete the relevant components of the Business Problem Identification section of the “Capstone Project Thesis Template.”

Submit both the “Analytics Problem Statement” template and the updated “Capstone Project Thesis Template.”

Prepare this assignment according to the guidelines found in the APA Style Guide, located in the Student Success Center. An abstract is not required.

This assignment uses a rubric. Please review the rubric prior to beginning the assignment to become familiar with the expectations for successful completion.

You are required to submit this assignment to LopesWrite. Refer to the LopesWrite Technical Support articles for assistance.

 

MIS 690 Topic 2 CLC – Data Needs Identification and Data Acquisition

This is a Collaborative Learning Community (CLC) assignment.

Now that you have identified the business problem and translated it into an analytics problem, you can now identify the data needs and acquire the data.

Provide a draft outline that identifies the data needs and addresses the following questions:

  1. What is needed? Be specific for each variable (e.g., Monthly Sales last 12 months, Number of Monthly Customers last 12 months).
  2. How can the data be obtained? When can the data be obtained?
  3. For each data variable, identify the specific type: Are they measured data (continuous, e.g., how long does a customer stay in the retail store?) or counted data (discrete, e.g., how many customers came to the store from 1 p.m. to 2 p.m.?).
  4. Assess whether the available data can be used to address the specific analytics problem statement identified in the Topic 1 assignment.
  5. Provide the raw data that you will be using for subsequent assignments. Place the dataset into an Excel file. Ensure that column headers are provided that clearly identify the meaning of each data variable. As needed, provide the necessary information in the file so data values can be interpreted. If there are concerns about proprietary issues related to using company data, you can change your data set accordingly.

Synthesize the information from your draft outline to complete, in 750-1,000 words, the relevant components in the Data Understanding, Acquisition, and Preprocessing section of the “Capstone Project Thesis Template.”

Submit the draft outline, raw data Excel file, and the updated “Capstone Project Thesis Template.”

Prepare this assignment according to the guidelines found in the APA Style Guide, located in the Student Success Center. An abstract is not required.

This assignment uses a rubric. Please review the rubric prior to beginning the assignment to become familiar with the expectations for successful completion.

You are required to submit this assignment to LopesWrite. Refer to the LopesWrite Technical Support articles for assistance.

 

MIS 690 Topic 3 CLC – Data Cleansing and Data Summary

This is a Collaborative Learning Community (CLC) assignment.

Now that you have identified the business problem, translated it into an analytics problem, identified the data needs, and acquired the data, you will use data that you have found (or with the company’s permission you can use its data for analysis) to resolve the analytics problem. Using one or more of the following software applications (IBM SPSS Modeler, SPSS Statistics, Excel, PowerBI, Tableau, or R), analyze the data so that the findings can be used to address the established business problem in your company.

Conduct an exploratory data analysis and provide a draft outline describing the key features of the data and any significant relationships and information contained in the data set that you found. You are required to include specific screenshots of graphs, tables, etc., that are provided:

  1. How did you verify that the data was reliable before proceeding?
  2. What problems did you find and how did you address them?
  3. What relationships did you find in the data?
  4. Are there any missing data?
  5. How are you going to summarize data samples?
  6. Analyze trends with respect to any appropriate characteristics that you may have discovered. Include relevant line graphs, pie charts, bar charts, and scatter plots.
  7. What have you done to prevent the Simpson’s paradox?
  8. Next, you will work on a descriptive analytics. Supplement your description with appropriate charts/figures and finalize by creating an appropriate dashboard with PowerBI or Tableau. Include a summary that provides a detailed overview of the data behavior you have identified based upon the analysis. Indicate any causal relationships you found.
  9. Segment the data accordingly, if needed, to help describe the data behavior. Did you have to redo your sample? Can you identify any data anomalies? If there are anomalies, what do they represent and how do you avoid them?
  10. Indicate the steps you have taken to investigate the quality of the data and indicate any variables you have transformed or discarded as a result.

Provide the raw software files (Tableau or PowerBI) that you used for this assignment.

Synthesize the information from your draft outline to complete, in 1,500–2,000 words, the relevant components in the Data Diagnostics and Descriptive Summary section of the “Capstone Project Thesis Template.”

Submit your draft outline, raw data Excel files, screenshots, and the updated “Capstone Project Thesis Template.”

Prepare this assignment according to the guidelines found in the APA Style Guide, located in the Student Success Center. An abstract is not required.

This assignment uses a rubric. Please review the rubric prior to beginning the assignment to become familiar with the expectations for successful completion.

You are required to submit this assignment to LopesWrite. Refer to the LopesWrite Technical Support articles for assistance.

 

MIS 690 Topic 3 Benchmark – Model Building

Utilizing the information from previous topics build a model that will solve the identified problem. This model should be an individual approach to apply an analytical process to effectively build a model that best fits the business problem. Use one or more of the following software applications: IBM SPSS Modeler, SPSS Statistics, Excel, Tableau, Python, or R.

Create a draft outline describing your model and addressing the following:

  1. Demonstrate your application of data analysis process by specifying which models you built and indicate why this best addresses the business problem.
  2. What variables did you include or leave out and why?
  3. Provide specific screenshots from the modeling software.
  4. Provide the raw software files that you used for this assignment.

Synthesize the information from your draft outline to complete, in 750-1,000 words, the relevant components in the Methodology Approach and Model Building section of the “Capstone Template.”

Submit the draft outline, raw data Excel files, screenshots, and the updated “Capstone Project Thesis Template.”

Prepare this assignment according to the guidelines found in the APA Style Guide, located in the Student Success Center. An abstract is not required.

This assignment uses a rubric. Please review the rubric prior to beginning the assignment to become familiar with the expectations for successful completion.

You are required to submit this assignment to LopesWrite. Refer to the LopesWrite Technical Support articles for assistance.

Benchmark Information

This benchmark assignment assesses the following programmatic competencies:

MS Business Analytics

1.5: Effectively apply data analytics processes.

 

MIS 690 Topic 4 Benchmark – Model Building

Utilizing the information from previous topics build a model that will solve the identified problem. This model should be an individual approach to apply an analytical process to effectively build a model that best fits the business problem. Use one or more of the following software applications: IBM SPSS Modeler, SPSS Statistics, Excel, Tableau, Python, or R.

Create a draft outline describing your model and addressing the following:

  1. Demonstrate your application of data analysis process by specifying which models you built and indicate why this best addresses the business problem.
  2. What variables did you include or leave out and why?
  3. Provide specific screenshots from the modeling software.
  4. Provide the raw software files that you used for this assignment.

Synthesize the information from your draft outline to complete, in 750-1,000 words, the relevant components in the Methodology Approach and Model Building section of the “Capstone Template.”

Submit the draft outline, raw data Excel files, screenshots, and the updated “Capstone Project Thesis Template.”

Prepare this assignment according to the guidelines found in the APA Style Guide, located in the Student Success Center. An abstract is not required.

This assignment uses a rubric. Please review the rubric prior to beginning the assignment to become familiar with the expectations for successful completion.

You are required to submit this assignment to LopesWrite. Refer to the LopesWrite Technical Support articles for assistance.

Benchmark Information

This benchmark assignment assesses the following programmatic competencies:

MS Business Analytics

1.5: Effectively apply data analytics processes.

 

MIS 690 Topic 5 CLC – Model Evaluation

This is a Collaborative Learning Community (CLC) assignment.

In this assignment, you will evaluate the individual models developed in the Topic 4 Model Building assignment and select the best model and approach to solving the identified business problem. Use the same software that you used in the Topic 4 Model Building assignment to evaluate the model. Include screenshots from the modeling software.

Create a draft outline describing how you evaluated the various models and singled out the best approach. Include the following:

  1. Describe the evaluation model that was used and explain why this model was selected.
  2. Can you validate your model? If the model cannot be validated, explain why. (Specific justification is needed here.)
  3. How did you validate the model? What specific approach was taken and why? For example, this could be a holdout or cross validation.
  4. What were the results of the validation?
  5. Provide specific screenshots.
  6. Provide the raw software files that you used for this assignment.

Synthesize the information from your draft outline to complete, in 750-1,000 words, the relevant components in the Model Evaluation section of the “Capstone Project Thesis Template.”

Submit the draft outline, raw data Excel files, screenshots, and the updated “Capstone Project Thesis Template.”

Prepare this assignment according to the guidelines found in the APA Style Guide, located in the Student Success Center. An abstract is not required.

This assignment uses a rubric. Please review the rubric prior to beginning the assignment to become familiar with the expectations for successful completion.

You are required to submit this assignment to LopesWrite. Refer to the LopesWrite Technical Support articles for assistance.

 

MIS 690 Topic 6 CLC Calibration and External Validation Literature Review

This is a Collaborative Learning Community (CLC) assignment.

Review the article, “Validate to Bring Out the Real Value of Visual Analytics,” provided in the study materials, for an in-depth understanding of expert validation, predictive validation, external validation, and cross validation.

Conduct a literature review of similar research to compare the model that you completed in Topic 5.

Create a draft outline with the following items in your literature review.

  1. Complete an external and cross validation.
  2. Explain if your validation method is still sufficient and discuss if the model results are consistent with theories in your field.
  3. What are the next steps for your model? Be specific.
  4. Is there a need for a model revision? If so, describe what shortcomings you encountered. If not, describe why.
  5. What future recommendations would you make to your model if you had another opportunity? What would you do differently?
  6. You are required to include at least three scholarly peer-reviewed sources.

Synthesize the information from the draft outline to complete, in 750-1,000 words, the relevant components of the External Model Verification and Calibration section of the “Capstone Project Thesis Template.”

Submit both the draft outline and the updated “Capstone Project Thesis Template.”

Prepare this assignment according to the guidelines found in the APA Style Guide, located in the Student Success Center. An abstract is not required.

This assignment uses a rubric. Please review the rubric prior to beginning the assignment to become familiar with the expectations for successful completion.

You are required to submit this assignment to LopesWrite. Refer to the LopesWrite Technical Support articles for assistance.

 

MIS 690 Topic 7 CLC Model Deployment and Model Life Cycle

This is a Collaborative Learning Community (CLC) assignment.

Create a draft outline describing the model deployment and model life cycle aspects of your model. Include the following:

  1. What are model deployment costs? Research and describe two similar models for cost benchmarks.
  2. What is a proposed task and timeline for deploying your model? Create a schedule using MS Project 2016 or another free software app.
  3. What specific training will be required for those who will be using the model on a regular basis? Be sure to review and reference the Topic 7 study materials related to models.
  4. Can this model be used on a repetitive basis? Explain.
  5. How will model quality be tracked over time? Be sure to review and reference the Topic 7 study materials related to models.
  6. What specific benefits to the organization will be realized over time as a result of using the model? Be sure to review and reference the Topic 7 study materials that cover cost and benefit analysis.

Synthesize the information from the draft outline to complete, in 750-1,000 words, the relevant components of the Model Deployment and Model Life Cycle section of the “Capstone Project Thesis Template.”

Submit the draft outline, raw data Excel files, screenshots, and the updated “Capstone Project Thesis Template.”

Prepare this assignment according to the guidelines found in the APA Style Guide, located in the Student Success Center. An abstract is not required.

This assignment uses a rubric. Please review the rubric prior to beginning the assignment to become familiar with the expectations for successful completion.

You are required to submit this assignment to LopesWrite. Refer to the LopesWrite Technical Support articles for assistance.

 

MIS 690 Topic 8 CLC Final Capstone Project Thesis

This is a Collaborative Learning Community (CLC) assignment.

Finalize your Capstone Project Thesis by refining your previous work on the “Capstone Project Thesis Template” completed in conjunction with the Topic 1-7 assignments. The Capstone Project Thesis should be 30-60 pages and organized according to the following:

  1. Business Problem and supporting information (based on work in Topic 1).
  2. Analytics Problem and supporting information (based on work in Topic 1).
  3. Results of Data Diagnostics and Descriptive Summary and associated supporting information (based on work in Topic 3).
  4. Methodology Approach and Model Building and associated supporting information (based on work in Topic 4).
  5. Model Evaluation (based on work in Topic 5).
  6. External Model Verification and Calibration (based on work in Topic 6).
  7. Model Deployment and Model Life Cycle (based on work in Topic 7).
  8. Recommendations for practice, future research, and conclusions.

Prepare this assignment according to the guidelines found in the APA Style Guide, located in the Student Success Center. An abstract is not required.

This assignment uses a rubric. Please review the rubric prior to beginning the assignment to become familiar with the expectations for successful completion.

You are required to submit this assignment to LopesWrite. Refer to the LopesWrite Technical Support articles for assistance.

 

MIS 690 Topic 8 Benchmark Capstone Project Presentation Recommendations and Reporting

Create a PowerPoint presentation of 10 to 15 slides, not including the title or reference slides. Utilize the “Capstone Project Thesis Template” as a guide for organizing your presentation. However, summarize your thesis specifically addressing your process for building, validating, testing, and applying of your model and tailor your presentation specifically for senior management. Your presentation should include how you determined that your analytics solutions addressed the specific business problem and conclude with specific future challenges and concluding recommendations. The presentation should be professional and should clearly communicate the results of the analytic models to the intended stakeholders.

You are required to include talking points in the “Notes” section of each slide. These notes should provide information that would be verbally conveyed when delivering the presentation in person.

Additionally, the last slides of your presentation are required to include references you have been acquiring from your Capstone Project Thesis.

Refer to the resources, “Creating Effective PowerPoint Presentations,” located in the Student Success Center, for additional guidance on completing this assignment in the appropriate style.

While APA style is not required for the body of this assignment, solid academic writing is expected, and documentation of sources should be presented using APA formatting guidelines, which can be found in the APA Style Guide, located in the Student Success Center.

This assignment uses a rubric. Please review the rubric prior to beginning the assignment to become familiar with the expectations for successful completion.

You are not required to submit this assignment to LopesWrite.

Benchmark Information:

This benchmark assignment assesses the following programmatic competencies:

MS Business Analytics

1.3: Build, validate, test, and apply analytics models.

2.2: Determine optimal analytics solutions to address specific business needs.

2.4: Communicate results of analytics analytical models to multiple stakeholders.

 

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MIS 690 All Week Assignments GCU

Best MIS 690 All Week Assignments GCU
MIS 690 All Week Assignments GCU

ACCT 553 DeVryBIAM 500 DeVryCIS 500 STRCIS 558 STRENG 105 GCUFIN 390 DeVryFIN 504 GCUHCA 545 GCUHCA 699 GCUHLT 306 GCUHLT 362 GCUHLT 555 GCUHLT 610 GCUHLT 665 GCUHOSP 594 DeVryHRM 600 DeVryMAT 144 GCUMGMT 600MGT 599 STRMGT 655 GCUMKT 373 GCUPSY 362 GCUPSY 565 GCUPSY 575 GCUPSY 665 GCUSOC 102 GCUSOC 320 GCUSOC 372 GCUSOC 412 GCUNSG 6440 SUHIM 515 GCUNSG 4029 SUHIM 615 GCUNSG 3029 SUNSG 4055 SUNSG 6630 SUNSG 6005 SUCRMJ 310PSY 510 GCUCRMJ 300 DevryCRMJ 425SPD 200 GCU, HLT 490 GCU ,ECH 340 GCU , ECH 440 GCU , ECH 355 GCU ,ECH 350 GCU ,LDR 461 GCU ,ECH 425 GCU ,REL 212 STR ,SCI 115 STR ,CIS 505 STR ,JUS 652 GCUMGT 640 GCUCIS 527 STRSOC 436 GCU,ACC 502 GCUFIN 504 GCU ,MATH 260 DeVry ,ETHC 445 DeVry ,ECET 220 DeVry , CARD 405 DeVryNETW 203 DeVryNETW 205 DeVryECET 365 DeVry ,MATH 270 DeVry ,PHYS 310 DeVry, BIB 106 GCU ,CIS 512 STR ,SYM 506 GCU ,ECN 601 GCU  ,BIAM 570 DeVryPSY 402 GCU , SOC 480 GCU , HUM 112 STR , PHI 210 STR,  ACC 667 GCU,  ACC 622 GCU,  ACC 623 GCU,  ENTR 510 DeVryDNP 840 GCU , BIO 550 GCU , HRM 420 DeVry , ACC 690 GCU  , HCA 807 GCU , ACC 650 GCU , REET 420 DeVry , MIS 605 GCU , ECET 350 DeVry , ENTR 530 DeVry , PSY 102 GCU , MIS 600 GCU , TCH 539 GCU , SPD 300 GCU , HCA 812 GCU , TCH 520 GCU , MGT 410 GCU , MIS 610 GCU , ELM 351 GCU

 

 

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