Use business knowledge, data analytics method, and data visualization skills to analyze the sales data from a music store. You can use any statistical tools you like, e.g. Excel, Python, R.<\/p>\n
Dataset<\/strong> Transactions Table<\/strong> Demographics Table<\/strong> <\/p>\n Requirements:<\/p>\n Please be creative and provide any writeups with graphs, dashboards, mathematical analysis as you see necessary to provide as many interesting insights as you can discover.<\/p>\n Here\u2019s a list of things you may consider when composing your writeup:<\/p>\n 1. Covert the \u2018Date of Transaction\u2019 column in the Transaction table to the standard datetime format.<\/p>\n 2. Merge two tables into one spreadsheet. (hint: v-lookup function in excel)<\/p>\n 3. Check the distributions of each column. Clean the dataset if there is a wrong record or outlier.<\/p>\n 4. What is the revenue trend over the months of the music store?<\/p>\n 5. Is the music store getting enough visitors?<\/p>\n 6. How many of the visitors are buying?<\/p>\n 7. Are men and women different in terms of total revenue, total visits, total transactions, or the number of albums purchased?<\/p>\n 8. Are men and women different in terms of average revenue, visits, or transactions per customer?<\/p>\n 9. Are men and women different in terms of revenue and transactions each month?<\/p>\n 10. The ultimate goal of the music store is to increase sales. Do you have any marketing strategy for the music store?<\/p>\n 11. Provide the finished dataset with your analytic results as the attachment in addition to the written assignment.<\/p>\n <\/p>\n Submitting requirement:<\/p>\n The cover page and reference page\/s are not included in the above-stated page requirement. These should be in addition to page requirements.<\/p>\n Format in proper APA 7th Edition style.<\/p>\n A minimum of three outside peer-reviewed sources for your references<\/p>\n","protected":false},"excerpt":{"rendered":" Use business knowledge, data analytics method, and data visualization skills to analyze the sales data from a music store. You can use any statistical tools you like, e.g. Excel, Python, R. Dataset The dataset records the sales revenue of a music store from January 1997 to June 1998. The dataset has two tables: Transactions and […]<\/p>\n","protected":false},"author":3,"featured_media":0,"comment_status":"open","ping_status":"closed","template":"","meta":[],"disciplines":[533],"paper_types":[],"tagged":[],"aioseo_notices":[],"_links":{"self":[{"href":"https:\/\/www.goodacademic.com\/blog\/wp-json\/wp\/v2\/questions\/6495"}],"collection":[{"href":"https:\/\/www.goodacademic.com\/blog\/wp-json\/wp\/v2\/questions"}],"about":[{"href":"https:\/\/www.goodacademic.com\/blog\/wp-json\/wp\/v2\/types\/questions"}],"author":[{"embeddable":true,"href":"https:\/\/www.goodacademic.com\/blog\/wp-json\/wp\/v2\/users\/3"}],"replies":[{"embeddable":true,"href":"https:\/\/www.goodacademic.com\/blog\/wp-json\/wp\/v2\/comments?post=6495"}],"version-history":[{"count":0,"href":"https:\/\/www.goodacademic.com\/blog\/wp-json\/wp\/v2\/questions\/6495\/revisions"}],"wp:attachment":[{"href":"https:\/\/www.goodacademic.com\/blog\/wp-json\/wp\/v2\/media?parent=6495"}],"wp:term":[{"taxonomy":"disciplines","embeddable":true,"href":"https:\/\/www.goodacademic.com\/blog\/wp-json\/wp\/v2\/disciplines?post=6495"},{"taxonomy":"paper_types","embeddable":true,"href":"https:\/\/www.goodacademic.com\/blog\/wp-json\/wp\/v2\/paper_types?post=6495"},{"taxonomy":"tagged","embeddable":true,"href":"https:\/\/www.goodacademic.com\/blog\/wp-json\/wp\/v2\/tagged?post=6495"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}
\nThe dataset records the sales revenue of a music store from January 1997 to June 1998. The dataset has two tables: Transactions and Demographics.<\/p>\n
\nExplanation of columns:<\/strong>
\nCustomer ID: the unique ID of each customer.
\nDate of Transaction: the date that the customer purchased the album.
\n# of Albums: the number of albums that the customer purchased.
\n$ Sales Revenue: the revenue of each transaction.<\/p>\n
\nExplanation of columns:<\/strong>
\nCustomer ID: the unique ID of each customer.
\nGender: gender information of each customer.
\nTotal Visits: the total number of visits of each customer to the music store.<\/p>\n