Business Strategy

For writing assignments, use UCO library resources (https://library.uco.edu/business) to access online library and databases. Students should reduce the amount of direct or indirect quotes to be less than 20% (twenty percent). The integrated software TurnItIn in assignment drop boxes of D2L automatically reviews student submissions and generates a similarity report for a submission. Please adhere to the following guidelines for writings:

• Refer to D2L for the full instruction of each assignment.
• A minimum of two hundred (200) words per question. For example, if an assignment requires three questions, the minimum total word count of the assignment is 200 x 3=600 words.
• A minimum of one (1) PRJ for the entire assignment.
• Submission files are of Microsoft Word format. Other file formats including PDF will not be graded.
• Refer to the assignment rubric in D2L for grading criteria. If you need clarification, consult the instructor before you work on the assignment.
• Ideas and contents that originate from other authors’ published media have to be cited. Refer to APA (https://apastyle.apa.org) for in-text citations and references. Papers with uncited materials in the main body or supplementary items that are from other authors’ published media will receive a zero grade. A sample of in-text citations and peer-reviewed journal reference list at the end of a writing is available in D2L for your reference. BOTH in-text citations and a reference list at the end of writing are required. Incomplete or incorrect formats of in-text citations and reference list at the end is considered as no in-text citations or no reference list.
• Use peer-reviewed journal (PRJ) reference. Use UCO library database such as ProQuest, ABI/INFORM, Academic Search Premier to find relevant peer-reviewed journal articles (PRJ). Wikipedia, the textbook, other books, white paper, trade magazine, trade journals, newspapers, white papers, working papers, or website information is NOT PRJ citation/reference.
• Using papers that have been previously submitted for other purposes will receive a zero grade.
• For verbatim citations (i.e., word-to-word copies), use double quotations and provide the citation including the page number in parenthesis.
• Provide a reference list at the end of an assignment write-up.
• Clearly label which part of the answer is for which question in the case study. There is no need to repeat the questions. Just clearly indicate which questions are being answered.
• Use only the D2L drop box tool to submit assignments. For research papers, the TurnItIn softwarewill be used to check for plagiarism. Students do not need to set up a separate account with TurnItIn since the software is integrated with D2L and has been turned on. A similarity report will be generated automatically. Students can view their similarity reports by clicking their submission links. Depending on the system load, it may take up to 24 hours for TurnItIn to generate similarity reports. Students should take into consideration of the possible lead time for getting their similarity reports. Students should view the similarity report. If the similarity score is higher than 20%, the submission needs to be revised to meet the 20% threshold. Students can achieve this goal by writing the critical analyses in their own words to avoid citing word-for-word definitions or copying/pasting from any research sources from the Internet, student papers, or past-class papers, etc. Submissions without a similarity report or with a similarity score of higher than 20% as reported by TurnItIn will NOT be graded and will receive a zero. There is no exception to this policy. To minimize the similarity score, don’t repeat the original questions in the answer. Just clearly indicate which part of the answer is for which question by providing the appropriate question number or just provide some key words from the question before an answer.
HW4: Big Data, Big Business, Big Opportunities. Pages 258-259. Answer any 3 questions for the “Big Data, Big Business, Big Opportunities” case on page 259.
page 259:
Big Data, Big Business, Big Opportunities
Imagine working 10 years to become the lead marketing executive at a large retail organization only to find that your competitor is invading your market share by 20 percent each year. You quickly decide to launch several online marketing promotions while improving your products but find your efforts are fruitless as your competitor continues to steal your customers, destroying your profits while raising its own.
As you begin to analyze your competitor’s business strategy, you find that while you were focused on sales reports, product inventory analysis, and other traditional marketing efforts, your competitor was making a massive investment in upgrading all of its management information systems. This included systems capable of collecting, storing, and analyzing data from every store, product, and sales representative in the market. In fact, your competitor now knows more about your products and sales cycles than you do. The new systems collect data not only throughout your competitor’s company but also from a group of suppliers, retailers, and distributors around the globe. These new systems provide your competitor with the ability to adjust prices instantly based on daily customer traffic patterns, reorder automatically from every entity in the supply chains, and even move items within a store or between stores for maximum selling efficiencies.
Your competitor has won, and not because it had a higher-quality product or better sales and marketing strategies, but because it identified the value of management information systems coupled with the ability to instantly access big data within and beyond the organization. You quickly realize that your competitor’s agility simply cannot be mimicked, offering it a huge competitive advantage. You sigh as you realize your company is in big trouble because it did not understand the dynamics of the big data age.
We are all familiar with the information age and the improvements made to organizations around the world as they are able to better manage employees, track sales data, and analyze customer purchasing patterns. However, this scenario is an example of the game-changing impact of big data, the massive amounts of data being collected by humans and machines over the last few years. Companies are now capturing hundreds of terabytes of data on everything from operations and finances to weather patterns and stock market trends. Sensors are now embedded in everything from products and machines to store floors, collecting real-time data on operations and customers. Radical customization, continuous experimentation, and information-driven business models are the new trademarks of competition as organizations analyze massive volumes of data. Data volumes are exploding, and more data has been created in the past 2 years than in the entire previous history of the human race. Here are the top 20 facts every manager should know about big data, according to Forbes magazine.3
■ Data is growing faster than ever before. In 2021, 2 megabytes of new information is created every second for every human being on the planet.
■ Every second we create new data. For example, we perform 40,000 search queries every second (on Google alone), which totals 3.3 billion searches per day, or 1.2 trillion searches per year.
■ In 2021, over 2.8 billion people used Facebook each day.
■ Facebook users send, on average, 31.25 million messages and view 2.77 million videos every minute.
■ Every minute, up to 300 hours of video are uploaded to YouTube alone.
■ 3 billion smart phones are shipped yearly—all packed with sensors capable of collecting all kinds of data, not to mention the data the users create themselves.
■ Distributed computing (performing computing tasks using a network of computers in the cloud) is real. Google uses it every day to involve about 1,000 computers in answering a single search query, which takes no more than a second to complete.
Questions

1. List the reasons a business would want to display information in a graphical or visual format.
2. Explain how issues with low-quality data will impact big data.
3. Explain how a marketing department could use data visualization tools to help with the release of a new product.
4. Categorize the five common characteristics of high-quality data and rank them in order of importance for big data.
5. Develop a list of some possible entities and attributes located in a marketing database.
6. Assess how a business could use a few of the data analysis techniques to understand how the business is operating.