This supply chain task is a real-world case study for a company we will call National Motors. National Motors has acquired a small firm called Kansas City

Motors. National Motors collects motors sold and runs monthly inventory reports to project motor inventory for future sales. This data represents inventory not sales and will support their predictive analysis.

You are a data analyst for a company. Your mentor has given you the opportunity to create a mock presentation that addresses the merger to support your professional development and give you feedback. Your mentor has also informed you that if your work exceeds expectations, it will be included in a presentation to the data analytics management team prior to their next steps.

Your mentor has given you an organizational problem and supporting materials in the form of a data set. National Motors and Kansas City Motors collect and store their data in different ways or use different databases.

The data from the two companies must be merged into a single database while maintaining data integrity and reliability. Your task is to assess a sample of data from the two companies in order to populate a gap analysis in Project Two. Specifically, examine the data provided in the Kansas City and Warehouse Data Set and the Kansas City Monthly Totals documents to address the organizational problem by probing the supporting materials forproblem by probing the supporting materials for anomalies due to the following:

• Different databases
• Data that is stored in different formats

You will also record the organizational issue, keep a list of solutions that need to be taken, and make note of the resolutions that are desired. Document all the steps you have taken from the objective to the data visualization.

Directions

For this project, you will create a preliminary assessment of the organizational challenge. For each topic, write one to two paragraphs that detail your findings. Specifically, you must address the following critical elements:

• Determine whether preliminary data represents/identifies the organizational challenge.
• Assess your data to see if it represents your organizational problem. Be sure to address the various differences and similarities when assessing each company's data reporting.
• Determine if the data is relevant to the organizational problem. Data should be directly related to the problem that is being addressed. Describe how the data does ordoes not support the problem.
• whether the data is usable or able to be analyzed.
• Determine if the data can be used for the gap analysis.
• Verify whether the data sets contain any "dirty data" that needs to be cleaned. There are times where data may need to be cleaned prior to analysis. In this topic, discuss why this process is important.
• Discuss the compatibility of the data formatting from both companies and what would need to happen to be able to merge them.
• Assess the preliminary data set for completeness and accuracy.
• Examine each data set for fitness of use. While reviewing the data, determine if each dataset meets the following criteria:
• Are there data values that are missing or unusable?
• Does the data represent the time period for which it is needed?
• Should the data values have a specified format? Are the values recorded in those formats?
• Do the data objects each represent a unique piece of the data, or are there musticle instances of the same datamultiple instances of the same data objects within a given data set?
• • Do data objects accurately represent the values expected? Are there outliers or anomalies?
  • Describe situations in which found errors could have been introduced and how those situations could be prevented after the merger.
  • Determine which data should be retained or analyzed to address the organizational challenge.
  • Determine what data you have and what you need from the data sets between the two companies. Some data may not be relevant to the situation as a whole, and some data may not specifically represent the problem being addressed. Identify what is needed within the data set and what needs to be removed. Keep the following points in mind:
  • Data that is not relevant to the problem
  • Data that does not represent the needs for this issue
  • Junk data and how it should be handled (i.e., keep, store, or remove)
  • Identify limitations for data usage in regard to regulatory, ethical, and legal considerations.
  • Identify the limitations that apply to the data that you have or need. Some data may be illegal to share in certain situations, and some companies may have policies against sharing data across departments.
  • Consider the following questions:
  • Is the data that is required accessible for analysis?
  • Are there ethical reasons that prohibit the collection and storage of certain data?
  • Is it legal to share data or have specific required data given the potentially varied audience?

Use the information in this document to help complete Project One. - In the 1st month, the Kansas City facility sold 3,120 motors. - In the 2nd month, the Kansas City facility sold 3,090 motors. - In the 3rd month, the Kansas City facility sold 3,140 motors. - In the 4th month, the Kansas City facility sold 3,010 motors. - In the 5 th month, the Kansas City facility sold 2,900 motors. - In the 6 th month, the Kansas City facility sold 2,990 motors. - In the 7th month, the Kansas City facility sold 3,000 motors. - In the 8 th month, the Kansas City facility sold 3,030 motors. - In the 9th month, the Kansas City facility sold 3,050 motors. - In the 10th month, the Kansas City facility sold 2,970 motors. - In the 11 th month, the Kansas City facility sold 2,980 motors. - In the 12 th month, the Kansas City facility sold 3,020 motors. - In the 13 th month, the Kansas City facility sold 3,100 motors. - In the 14th month, the Kansas City facility sold 2,900 motors. - In the 15th month, the Kansas City facility sold 3,000 motors. - In the 16th month, the Kansas City facility sold 3,040 motors. - In the 17 th month, the Kansas City facility sold 3,060 motors. - In the 18th month, the Kansas City facility sold 2,950 motors. - In the 19th month, the Kansas City facility sold 2,970 motors. - In the 20th month, the Kansas City facility sold 2,990 motors. - In the 21 st month, the Kansas City facility sold 3,000 motors. - In the 22nd month, the Kansas City facility sold 3,000 motors. - In the 23rd month, the Kansas City facility sold 3,010 motors. - In the 24th month, the Kansas City facility sold 2,980 motors. - In the 25th month, the Kansas City facility sold 2,965 motors. - In the 26th month, the Kansas City facility sold 2,945 motors. - In the 27 th month, the Kansas City facility sold 2,923 motors. Addendum: Late entry - In the 28 th month, the Kansas City facility sold 286 motors. Ao