Data measurement is an important aspect of data analytics
Data measurement is an important aspect of data analytics. Identifying trends in key attributes of data is a fundamental measurement for various aspects in business data and an important skill for business professionals. In this scenario, you are a business consultant trainee assigned to work with your first client, a superstore. The superstore is looking to see if there are specific trends that could be identified to help them improve their operations and sales and grow their business. You will report to your company’s vice president of operations. Periodically, you will be expected to apply your training and submit a deliverable to the vice president.The superstore has provided you with a data set, Superstore Excel Workbook, that contains data about orders over a span of three to four years. They have asked you to calculate measures of central tendency of their data using the mean, mode, and median for the following attributes: sales, quantity, discount, and profit. This will provide you with a snapshot of the data to begin your analysis. As a business consultant, you need to be able to look at data and understand what it presents for analysis.You will first explain the data and its attributes in a short report. Once you have created a table and calculated the central tendency, you will produce visual representations for the superstore to effectively and efficiently gain helpful insights into their data and its attributes. To accomplish this task, you will create charts to present the descriptive analysis you performed. You will continue to delve further into your analysis for this superstore throughout the course.
For this assignment, calculate the central tendency of the superstore data set using the mean, median, and mode. You will also create multiple charts to present the descriptive analysis you performed.
Explain the data and its key attributes.
Describe your general observations of the sales, quantity, discount, and profit attributes and their relationship to other attributes within the data set.
For example, if you are describing sales, what trends across other attributes are you seeing (sales as they relate to region, sales as they relate to product category, etc.)?