Data and Deliverables

1

IT Help Desk

The ABC Company’s CEO is interested in examining how quickly issues are resolved and improving customer satisfaction. Analyze the help-desk tickets, including number of tickets, number of high priority tickets, and average response time. Understand the causes of high-priority tickets, and improve resolution times with better understanding of ticket details.

The following information in this cell is from the IBM Watson Analytics website:

Background: This data is from an Information Technology (IT) department interested in examining how quickly issues are resolved and improving satisfaction of customers. To start their analysis, they have this data set of 100,000 closed tickets that were filed at their help desk.

About the data: A total of 100,000 rows. Each row in the data includes:

• employee who submitted the ticket
• employee’s seniority within the company
• IT employee who serviced the ticket
• functional area against which the ticket was filed (systems, software, hardware, access)
• whether the ticket was a request for new services or an issue with existing services
• submitter-assigned severity of the ticket
• IT-assigned priority of the ticket
• number of days the ticket was open
• satisfaction with the resolution of the ticket (reported by the submitter)

2

Employee Attrition

ABC Company’s CEO is curious to find the factors that lead to employee attrition. This will be very important as the CEO moves forward with the expansion of the company. The stakeholders are interested in this analysis, which will provide some insights into leadership effectiveness. The analysis should take some key point indicators (Distance, Education, Job Role, Income) and provide an analysis.

3

Telco Customer Churn

ABC Company’s CEO is concerned that, during this expansion, customers may leave the company for its competitors. Predict the behavior of customers and how to retain them. Analyze all relevant customer data and develop focused customer retention programs. 

The data set includes information about:

• Customers who left within the last month—this column is called Churn.
• Services that each customer has signed up for—phone, multiple lines, internet, online security, online backup, device protection, tech support, and streaming for TV and movies.
• Customer account information—how long they have been a customer, contract, payment method, paperless billing, monthly charges, and total charges.
• Demographic info about customers—gender, age range, and whether they have partners or dependents.

4

Accounts Receivable

In the past, ABC Company’s CEO had set up business accounts where the business could carry a balance with purchases (goods or services) that were made. Due to the expansion, the stakeholders are concerned that the balances will not be paid. The CEO would like to understand the factors of successful collection efforts. Predict which customers will pay fastest, recover more money, and improve collection efficiency.

5

Operations Dem Planning Bike Share

During this expansion investigation, ABC Company’s CEO would still like to manage the process of matching supply and demand. Explore information based on usage and external factors to understand the effects of a bike-share program in a major U.S. city to analyze patterns such as the relationship between humidity and ridership by month, or how temperature and holidays drive usage demand. 

6

Retail Sales and Marketing, Profit and Cost

During the expansion process, ABC Company’s CEO realizes that there will need to be a review of the product-related information, such as Cost, Revenue, and Price, across Years and Ordering Method. This will be especially important to the stakeholders, as they will see what has worked and what has not. This data set could be used to create a multiple-tab dashboard in Microsoft Power BI. For this data set, you will be an analyst for one of the stakeholders and find insights in Sales and Marketing, and Profit and Cost. The data is clean and manageable.

7

Marketing Campaign

ABC Company’s CEO is looking to add new items to the menu in the fast food department. The CEO needs help determining the promotion campaign for the new products. Quickly analyze test market campaigns based on responses, revenue, and other key metrics. Predict who will respond to which campaign by which channel, and why. Increase the likelihood of responses and the quality of leads in future campaigns. A different promotion is used at each location, and the weekly sales of the new item are recorded for the first four weeks.

• MarketID

Unique identifier for market (1–10).

• Market Size

Size of market area by sales (Small, Medium, Large).

• LocationID

Unique identifier for store location.

• Age Of Store

Age of store in years (1–28).

• Promotion

One of three promotions that was tested (1, 2, 3).

• week

One of four weeks when the promotions were run (1–4).

• Sales In Thousands

Sales amount for a specific LocationID, Promotion, and week.

Critical Elements

Exemplary

Proficient

Needs Improvement

Not Evident

Value

Report for Stakeholders:

Enterprise-Level

Report

Generates an enterprise-level report that is submitted along with the executive summary

(100%)

Generates an enterprise-level report that is submitted along with the executive summary, but the report is lacking in detail or contains inaccuracies

(55%)

Does not generate an enterprise-level report (0%)

3.96

Report for Stakeholders:

Executive Summary

Meets “Proficient” criteria, and the summary demonstrates keen insight into how to appropriately communicate the details of the report (100%)

Composes a detailed executive summary, utilizing audienceappropriate language, in which the process of creating the enterprise-level report and the visualizations used is explained, and defends the actions performed (85%)

Composes a detailed executive summary, but the summary lacks details about process or does not defend actions or does not use audienceappropriate language or contains inaccuracies (55%)

Does not compose an executive summary (0%)

3.96

Identify the Business

Question

Meets “Proficient” criteria, and explanation demonstrates sophisticated awareness of what data would be required to solve the business problem

(100%)

Selects a data set and scenario from the provided list and explains how to solve the business question and what sort of data would be required in order to do so (85%)

Selects a data set and scenario from the provided list and explains how to solve the business question and what sort of data would be required in order to do so, but explanation is cursory or contains inaccuracies (55%)

Does not select a data set and scenario from the provided list and does not explain how to solve the business question or what sort of data would be required in order to do so (0%)

3.96

Making Sense of

Data: Data

Correlates

Meets “Proficient” criteria, and explanation demonstrates a complex grasp of the correlation and relevance of the data to the business question (100%)

Explains what the data is and how the data correlates back to the business question (85%)

Explains what the data is and how the data correlates back to the business question, but explanation is cursory or contains inaccuracies (55%)

Does not explain what the data is and how the data correlates back to the business question

(0%)

5.94

Making Sense of

Data: Areas of Data

Meets “Proficient” criteria, and the defense demonstrates sophisticated awareness into why the particular data should be used (100%)

Explains which areas of data from the spreadsheet will be utilized and why (85%)

Explains which areas of data from the spreadsheet will be utilized and why, but the explanation is cursory or contains inaccuracies (55%)

Does not explain which areas of the data from the spreadsheets will be utilized (0%)

5.94

Business

Intelligence: Power

BI

Meets “Proficient” criteria, and explanation demonstrates a sophisticated awareness of how Power BI can be utilized as an analysis tool for addressing business problems (100%)

Explains how to address the organization's business problem using the Power BI analysis tool (85%)

Explains how to address the organization's business problem using the Power BI analysis tool, but explanation is cursory or contains inaccuracies

(55%)

Does not explain how to address the organization's business problem using the Power BI analysis tool (0%)

5.94

Business

Intelligence: Affect the Audience

Meets “Proficient” criteria, and explanation demonstrates a sophisticated awareness of how the Power BI analysis tool can influence and affect the audience (100%)

Explains how the Power BI analysis tool can influence and affect the audience (85%)

Explains how the Power BI analysis tool can influence and affect the audience, but explanation is cursory or contains inaccuracies (55%)

Does not explain how the Power BI analysis tool can influence and affect the audience (0%)

3.96

Software

Integration: Upload 

Data set was uploaded into Power BI using the correct data type and fields (100%)

Data set was uploaded into Power BI but does not use the correct data type, or fields are

not correct (55%)

Does not upload the data set into Power BI (0%)

7.92

Software Integration:

Appropriate

Formatting

Data has been edited, and columns have appropriate formatting (100%)

Data has not been edited, or columns do not have appropriate formatting (55%)

Data has not been edited and columns do not have appropriate formatting (0%)

7.92

Guiding Questions:

Develop Business

Questions

Developed business questions based on initial analysis that will effectively guide visualizations (100%)

Developed business questions based on initial analysis that will effectively guide visualizations, but questions are inappropriate or are not supported (55%)

Did not develop business questions (0%)

7.92

Guiding Questions:

Effectively Answer

Meets “Proficient” criteria and expertly explains how to effectively answer the business question (100%)

Explains how to use the compiled and cleaned data to effectively answer the business questions posed based on the initial analysis (85%)

Explains how to use the compiled and cleaned data to effectively answer the business questions posed, but explanation is cursory, lacks key details, or contains inaccuracies

(55%) 

Does not explain how to use the compiled and cleaned data to effectively answer the business question (0%)

5.94

Visualizations:

Displaying the Data

Meets “Proficient” criteria, and description demonstrates a sophisticated awareness of how the visualization is best suited for displaying data (100%)

Describes which particular visualization is best suited for displaying the data (85%)

Describes which particular visualization is best suited for displaying the data, but description is inaccurate or is not supported (55%)

Does not describe which particular visualization is best suited for displaying the data

(0%)

5.94

Visualizations:

Conveying

Information

Meets “Proficient” criteria, and description demonstrates a sophisticated awareness of how the visualization is best suited for conveying information

(100%)

Describes how the visualization used is best suited for conveying information to the targeted user audience and their interaction needs across multifunctional teams (85%)

Describes how the visualization used is best suited for conveying information to the targeted user audience and their interaction needs across multifunctional teams, but the description is cursory or contains inaccuracies (55%)

Does not describe how the visualization used is best suited for conveying information to the targeted user audience and their interaction needs across multifunctional teams (0%)

5.94

Visualizations:

Accurately Display

Generated visualizations to accurately display the data

(100%)

Generated visualizations to display the data, but data is not accurately displayed (55%)

Did not generate visualizations to display the data (0%)

5.94

Visualizations: Visual

Data Correlations

Create visual data correlations by integrating additional data into the visualizations (100%)

Create visual data correlations by integrating additional data into the visualizations, but visual data correlation is inaccurate (55%)

Does not create visual data correlations (0%)

5.94

Visualizations: Insert

Data Visualizations

Meets “Proficient” criteria, and explanation demonstrates keen insight into what the visualizations represent (100%)

Inserts data visualizations into report and explains what the visualizations represent (85%)

Inserts data visualizations into report, but explanation is cursory, contains inaccuracies, or is incomplete (55%)

Does not insert data visualizations into report and does not explain what the visualizations represent (0%)

3.96

Actionable Insights

Identifies actionable insights based on analysis (100%)

Identifies actionable insights based on analysis, but insights are inaccurate or lack support

(55%)

Does not identify actionable insights based on analysis (0%)

3.96

Articulation of

Response

Submission is free of errors related to citations, grammar, spelling, syntax, and organization and is presented in a professional and easy-to-read

format (100%)

Submission has no major errors related to citations, grammar, spelling, syntax, or organization

(85%)

Submission has major errors related to citations, grammar, spelling, syntax, or organization that negatively impact readability and articulation of main ideas (55%)

Submission has critical errors related to citations, grammar, spelling, syntax, or organization that prevent understanding of ideas (0%)

4.96

Total

100%