Category: Data Analytics

Data Analytics is the process of examining raw data to uncover patterns, draw meaningful insights and support better decision making. It helps individuals and businesses understand past performance, monitor current trends and predict future outcomes.. Features of Data Analytics are

• Insight Generation: Helps identify trends, patterns and anomalies in data to make informed decisions.
• Predictive Capabilities: Uses historical and current data to forecast future outcomes and opportunities.
• Data Management: Involves building systems and tools to efficiently handle, process and analyze large volumes of data

Overview:

A national company has been receiving customer complaints across a wide variety of products and services. To improve customer satisfaction and operational efficiency, the company needs an in-depth analysis of these complaints to identify patterns and actionable insights. Your task is to assist the company by creating an interactive Tableau dashboard and providing strategic recommendations based on your findings. Demonstrate original critical thinking and synthesis of ideas; reliance on AI-generated analyses is inappropriate and does not fulfill the requirements for graduate-level scholarship.

Background:

The company has provided a dataset containing information about customer complaints. This dataset includes various details such as the products involved, the nature of the complaints, how complaints were submitted, and the resolution provided. Your analysis will focus on uncovering trends, understanding customer priorities, and evaluating the companys responsiveness.

Dataset Description:

The dataset includes the following columns:

• Customer ID: A unique identifier for each customer.
• Product: The specific product associated with the complaint.
• Product Category: The broader category of the product.
• Issue: Description of the issue reported by the customer.
• Consumer Disputed?: Indicates if the consumer disputed the resolution (Yes, No, or Pending).
• Date Received: The date the complaint was received.
• Date Submitted: The date the complaint was submitted by the consumer.
• Submitted via: The channel through which the complaint was submitted (e.g., Website, Email, Phone).
• Tags: Priority level or special conditions (e.g., High Priority, Escalated).
• Timely Response?: Whether the company provided a timely response (Yes or No).
• ZIP Code: Customers ZIP code.
• Number of Complaints: Count of complaints submitted by the customer.
• State: The state where the customer resides.
• Company Response to Consumer: Outcome or resolution provided by the company.

Objectives:

Your goal is to analyze the dataset and provide actionable insights through an interactive Tableau dashboard. The final deliverable should help the company achieve the following:

• Identify trends and patterns in customer complaints.
• Understand which products and categories receive the most complaints.
• Evaluate the effectiveness of the company’s responsiveness and resolutions.
• Propose recommendations to enhance customer satisfaction.

Task:

Data Cleaning and Preparation:

• Ensure data consistency and accuracy.
• Handle missing values and correct any data inconsistencies.
• Derive additional columns if needed.

Dashboard Design:

• Design a dashboard that is clear, visually appealing, and easy to interpret, modeled after the example dashboard shown in the provided video.
• Use appropriate chart types, colors, and labels to enhance readability.

Analysis and Insights:

• Analyze the data and provide insights based on the visualizations.
• Identify trends, patterns, and any notable observations from the data.

Presentation:

• Prepare a brief report or presentation summarizing the findings.
• Include a 20 – 25 minute presentation video where you walk through the workings of the dashboard and a brief summary of the analysis. The presentation should cover:
• Overview of the Dashboard: Demonstrate the dashboard’s interactive features, functionality, and key insights.
• Data Sources and Preparation: Explain the data cleaning and preparation steps and highlight key aspects of your analysis.
• Detailed Walkthrough: Go through each visualization, explaining what it shows and why it is important.
• Key Insights and Observations: Summarize the main findings and insights from the data.
• Technical Aspects: Briefly discuss any technical challenges or interesting techniques used in creating the dashboard.

Supporting files: * Tableau dashboard file* Brief, 1-2 page executive report summarizing the findings

Submission: (submit all THREE items)

1. Tableau dashboard file

2. Prepare a brief executive report (1-2 pages) summarizing the findings.

3. Submit a video file demonstrating the dashboard’s interactive features, functionality, and key insights.

Any dashboard generated using AI will be marked zero.

Evaluation Criteria:

• Accuracy of data cleaning and preparation.
• Completeness and clarity of visualizations.
• Creativity and effectiveness of the dashboard design.
• Depth of analysis and quality of insights.
• Overall presentation and communication, including the effectiveness of the recorded presentation video.

Regression is an analytical technique used to make a relationship between input variables and continuous outcome variables.

A sample of data on cars is provided for this assignment. The file contains data on sales of used cars with 1436 records containing details. The attributes of the data include Age (Age in years), KM (Accumulated Kilometers on the odometer), HP (horsepower), CC (Cylinder Volume in cubic centimeters), Doors (Number of doors), Weight (Weight in Kilograms), and Price (Price of Cars). Run a multiple regression with the outcome variable Price and the predictor variables Age, KM, HP, CC, Doors, and Weight. (Using Python, Jupiter Notebook)

Before performing the analysis.

1. Perform descriptive analysis.
2. Perform correlational analysis and describe the analysis.
3. Apply standardization to the data.
4. Perform correlational analysis.
5. Split the data into a training set and a testing set of the data.
6. Perform multiple regression on the training set!
7. Perform
8. Explain the linear regression coefficient and intercept.
9. Specify the linear regression equation.
10. Perform model evaluation Mean Squared Error (MSE)

Include a brief description of each step and the screen print of your Python codes in your paper.

For this week’s discussion, you will discuss the following:

1. Name three types of Interactive Actions that you can add in a Dashboard. (Tableau)
2. What are some of the uses of these Actions?

Here is the material.

For this week’s discussion, you will discuss the following:

1. Name three types of Interactive Actions that you can add in a Dashboard. (Tableau)
2. What are some of the uses of these Actions?

Here is the material.

Data refers to raw, unorganized facts and figures, such as numbers, text, images, or symbols, that can be processed and analyzed to extract meaningful information

• Data can exist in a raw form (unorganized) or processed form (organized and meaningful).
• A database is a structured collection of data designed for efficient storage, retrieval and manipulation.
• It serves as a centralized repository, allowing data to be accessed, managed, and updated by multiple users or applications.
• A high-performing database is vital for any organization, supporting operations, customer interactions and systems like digital libraries, reservations, and inventory management. Databases are essential because they:
• • Scale efficiently to handle massive volumes of data.
  • Ensure data integrity through built-in rules and constraints.
  • Protect data with secure access controls and compliance support.
  • Enable analytics by identifying trends and guiding informed business decisions.

In this assignment you will 1) research the total debt D and 2) calculate the weighted yield to maturity R_D for your assigned corporation. To find R_D we must create a table in Excel. Note: If your corporation data has more than ten bonds, just choose any ten for your calculations in the Excel table. You will use your calculated R_D to complete the WACC calculation due next week.

STARBUCKS is my corporation

Click on the Symbol of two of your bonds. In a separate word document answer the following questions (feel free to copy/paste these into your word document):

1. Bond Maturity:
   1. What maturity date is farthest into the future? Approximately how many years (or months) from now?
   2. What maturity date is the next one to expire? Approximately how many years (or months) from now?
   3. Refer to Figure 7.2 on page 206 in the text. Of the two bonds above, which bond has the most interest rate risk?
2. The Call Provision:
   1. Are either of the bonds Callable?
   2. Click on the ^ in the Callable row. For callable bonds, is it important to consider your yield-to-call? Why?
   3. Refer to “The Call Provision” on page 215-216 of the text. True or False: In a “make-whole” call provision, the call price is higher when interest rates are lower and vice versa.
3. Total Debt:
   1. Since the debt D calculated in your excel table is only a sampling, you must find the total corporate debt elsewhere. Do a Google search for “Long Term Debt for ______” using your corporation name. You may also use any other source to find the Long Term Debt. Enter the web link and the Long Term Debt value here. You will use this total debt D to complete the WACC calculation due next week.
   2. You will see your company bond data in a table like the one below. Note that you must use the bottom scroll bar to see all the data. If your computer does not show the columns below, simply click on Columns to apply any missing columns. Make note of the Quantity, Price, and Yield data that appears. You will enter this data in your spreadsheet. You must click on the Symbol to get the answers required for the written part of this assignment.
      

   3. Read the Case Study detailing the creation of a baseball stadium. Define a list of the steps needed to build the stadium using the case study and add as much detail as needed. Be specific in your assumptions (days, hours worked, etc). With this information documented, create a Gantt chart and the critical path of the project. Your assignment should include a Gantt chart, clear identification of the Critical path, and a written paragraph defining your project assumptions and answering the questions presented in the case study. This goes with the gnat chart document assignment.

      The objective of ‘crashing’ is to reduce the time of a project at an acceptable additional cost. For this assignment, determine all possible paths use the information contained in the chart. Compress one time unit per move using the least cost method. Assume the total indirect cost for the project is $700 and there is a savings of $50 per time unit reduced. Record the total direct, indirect, and project costs for each duration.Show your work including your original options and any ‘crashing’ activity in detail.Questions to answer: this goes with the other document attached crash time exercise

      1. What is the optimum cost-time schedule for the project? (in units)
      2. What is the cost?

      ALL ASSIGNMENTS MUST HAVE SEPARATE DOCS

What can you learn about the causes of death for adults in the United States from and ? The data is available via the at the Center for Disease Control (CDC).

How has COVID-19 impacted this list? You can find multiple sources of COVID-19 data in the page in the top Module of this course.

Every set of data can tell many stories. You must analyze the data and select a story from the data. Never project your story onto the data. Focus your work on this case study on one story from the data. For example, suicide across age groups, sex, and ethnic groups. Yes. You can use that story or select a different story from the data.

Submit a report of fewer than eight pages. Use level one, two, and three headings as needed. Ensure you have an introduction and conclusion. Ensure you use visualizations (e.g. charts and graphs) to support your analysis. Ensure you properly cite visualizations you do not create.

Requirements

• APA version 7 format for the report.
  • Include a cover page and abstract.
  • Do not include a table of contents.
  • Use for guidance.
• Three scholarly citations in addition to the sources provided.
• Review the rubric to ensure you understand how you will be assessed.

References:
Heron, M. (2019). Deaths: Leading causes for 2017. National Vital Statistics Reports, 68(6). Retrieved from

Kochanek, K.D., Murphy, S.L., Xu, J., & Arias, E. (2019). Deaths: Final data for 2017. National Vital Statistics Reports, 68(9). Retrieved from

I uploaded the files which contains the Exercise and the other files to solve it.

Please adhere to the following:

1- Do not use artificial intelligence, as the university detects its use and has Turnitin.

2- Do not duplicate assignments from other students.

3- Submit within the specified timeframe,I have chosen two days.

i have done evreything i just want you to edit it i attached u the word document it have three questions i did one and 3 i want you to check what i miss also for calf 1 the day trading do 4 day trades one last week at january show that u trade per day 5 times she want more numbers more tables more explaining about them do search for both she want intext citatiation for calf 3 there is bullet points tooo much please not i dont want it like that and add more tables and graphs numbers she want these things important to finish it today take what the teacher wants on calf 1