Unit 9 Assignments
Assignment 1
Read the Case and answer questions below.
data-warehousing-and-multi-dimensional-data-modeling-case.pdf
SAGE Business Cases – Data Warehousing and Multi-Dimensional Data Modeling files.pdf
Then Answer the following:
- Describe the notion of grain or granularity, why is it important, how could it limit your functionality, time to develop, and cost of the project?
- From the case conclusion “What are the potential pitfalls in integrating a warehouse system with existing IT systems? Identify at least 3 and describe why they are pitfalls?
- Pick any 4 queries from the list below and identify which ODS (Operational Data Stores) must be accessed to answer the query (some available ODS are in the table following the queries, you can use others if need be.
Queries:
- Which are the Top-30 SKU’s by sales revenue, sales volume, and profitability?
- Which products and customers have the highest/lowest gross margins?
- What are the key sales and gross margin trends by product type, store, and geography?
- Which products were on promotions but did not sell? Slice and dice the data by geography, product
category and month. - What is my inventory turns and total days of supply? Analyze the trends by store, product and time.
- What is the total gross margin ROI for an SKU (e.g. Apple iPhone 6)? Rollup the data by product
category, time, and store.
ODS:
| CRM (Customer Relationship Management) |
| Sales By product, Store, |
| Purchase Orders |
| Inventory Data |
| Accounting (Invoices, and Accounts receivable, Profit and Loss by customer and product) |
Assignment 2
Read Chapter 11 of INFORMATION SYSTEMS: A MANAGER’S GUIDE TO HARNESSING TECHNOLOGY (Links to an external site.)
The Data Asset: Databases, Business Intelligence, and Competitive Advantage Sections 11.1 – 11.4
Information-Systems-A-Manager039s-Guide-to-Harnessing-Technology-1538497232 (3).pdf
Complete questions 1-5 at the end of section 11.3
Complete questions 2& 3 at the end of section 11.4
You will see a link to download the exercise files on the page lower right, you may have to scroll.
Follow Gini’s course in your own version of PowerBI, which you now have. When you complete chapter 3 you will have completed a PowerBI report with visualizations. Export your competed to PowerPoint selecting current values and upload the PowerPoint to complete the assignment.
Assignment 3
Read Chapter 10 of the Saylor book:
Business Intelligence: Analysis of App Sales Data
Business Information Systems.pdf Pages 172 – 192
Answer the following Questions
1. Managers are often most interested in exceptions—data that does not fit pre-established expectations.
Describe how business intelligence can aid in this process.
2. Why do lower level managers require higher level detail in their information?
3. Briefly explain the concept of latency in a Data Warehouse or BI application. How is it related to the frequency of transactions occurring? Is some degree of latency acceptable?
Assignment 4 PowerBI part 1
Log in to your Office 365 account you should see PowerBI as an option.
Log in to : https://linkedinlearning.psu.edu/ (Links to an external site.)
Access the Power BI course at: linkedin.com/learning/power-bi-essential-training-3/create-and-manage-dashboards? (Links to an external site.)
Take Gini von Courter’s course and complete:
Module 1 Get started with Power Bi
Module 2 Get Data
Module 3 Create a Report with Visualization
You will see a link to download the exercise files on the page lower right, you may have to scroll.
Follow Gini’s course in your own version of PowerBI, which you now have. When you complete chapter 3 you will have completed a PowerBI report with visualizations. Export your competed to PowerPoint selecting current values and upload the PowerPoint to complete the assignment.
Assignment 5 PowerBI part 2
Log in to your Office 365 account you should see PowerBI as an option.
Log in to : https://linkedinlearning.psu.edu/ (Links to an external site.)
Access the Power BI course at: linkedin.com/learning/power-bi-essential-training-3/create-and-manage-dashboards? (Links to an external site.)
Take Gini von Courter’s course and complete:
Module 4 Modify and Print a Report
Module 5 Create a Dashboard
You will see a link to download the exercise files on the page lower right, you may have to scroll.
Follow Gini’s course in your own version of PowerBI, which you now have. When you complete the last section of Module 5 you will have completed a PowerBI Dashboard. If you followed Gini’s instruction you should have a dashboard with your initials in front of it. (in the Example Gini’s is GVC Dashboard.) The is the last dashboard you work with in module. Share your Dashboard with me WHM13@psu.edu to complete the assignment.
BI Case
Read the case and answer questions 1,4, and 5 for class discussion. Please turn in for credit for the assignment.data-analysis-decision-making-re-accommodating-passengers-airline-co-case.pdf
Optional Cases
Call Center:
Vehicles Navistar:
Airports and Air Traffic:
A Manager’s Guide to Harnessing Technology 11.3
- Why would a firm use a loyalty card? What is the incentive for the firm? What is the incentive for consumers to opt in and use loyalty cards? What kinds of strategic assets can these systems create?
- In what ways does Tesco gather data? Can other firms match this effort? What other assets does Tesco leverage that helps the firm remain among top performing retailers worldwide?
- Make a list of the kind of data you might give up when using a cash register, a Web site, or a loyalty card, or when calling a firm’s customer support line. How might firms leverage this data to better serve you and improve their performance?
- Are you concerned by any of the data-use possibilities that you outlined in prior questions, discussed in this chapter, or that you’ve otherwise read about or encountered? If you are concerned, why? If not, why not? What might firms, governments, and consumers do to better protect consumers?
- What are some of the sources data aggregators tap to collect information?
A Manager’s Guide to Harnessing Technology 11.4
- Discuss the possible consequences of a company having multiple plants, each with a different information system using different part numbers and naming conventions for identical products.
- Why does it take longer, and require more processing power, to analyze sales trends by region and product, as opposed to posting a sales transaction?
A Manager’s Guide to Harnessing Technology 11.5
- List the issues that need to be addressed in order to design, develop, deploy, and maintain data warehouses and data marts.
- What is meant by “data relevance”?
- What is meant by “data governance”?
- What is the difference between a data mart and a data warehouse?
- Why are data marts and data warehouses necessary? Why can’t an organization simply query its transactional database?
A Manager’s Guide to Harnessing Technology 11.5
- Data relevance. What data is needed to compete on analytics and to meet our current and future goals?
- Data sourcing. Can we even get the data we’ll need? Where can this data be obtained from? Is it available via our internal systems? Via third-party data aggregators? Via suppliers or sales partners? Do we need to set up new systems, surveys, and other collection efforts to acquire the data we need?
- Data quantity. How much data is needed?
- Data quality. Can our data be trusted as accurate? Is it clean, complete, and reasonably free of errors? How can the data be made more accurate and valuable for analysis? Will we need to ‘scrub,’ calculate, and consolidate data so that it can be used?
- Data hosting. Where will the systems be housed? What are the hardware and networking requirements for the effort?
- Data governance. What rules and processes are needed to manage data from its creation through its retirement? Are there operational issues (backup, disaster recovery)? Legal issues? Privacy issues? How should the firm handle security and access?
References
2015, “A Manager’s Guide to Harnessing Technology“, University of Minnesota Libraries Publishing edition.
