DAD 220 Analysis and Summary Laboy

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Southern New Hampshire University *

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220

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Mechanical Engineering

Date

Dec 6, 2023

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docx

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2

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DAD 220 Analysis and Summary Template 1. Analyze the data you have been provided with to identify themes : a. Which parts are being replaced most? i. [Fuel Tanks.] b. Is there a region of the country that experiences more part failures and replacements than others? i. Identify region: 1. [MIDWEST] ii. How might the fleet maintenance team use the information to update its maintenance schedule? [By running the command finding how many repairs by parts can keep inventory up to of parts. SELECT repair AS PART_REPAIR, COUNT(*) AS NUMBER_OF_REPAIRS FROM parts_maintenance GROUP BY PART_REPAIR ORDER BY NUMBER_OF_REPAIRS DESC;] c. Which parts are being replaced most due to corrosion or rust? i. [Wheel Arch.] d. Which parts are being replaced most because of mechanical failure or accident, like a flat tire or rock through the windshield? i. [TIRE REPAIR] 2. Write a brief summary of your analysis using nontechnical language. a. [In running the analysis in car parts that have the most issue with rust, corrosion, cracks, flat and other parts with the table query we can find out where car have the most issues.] 3. Outline the approach that you took to conduct the analysis. a. What queries did you use to identify trends or themes in the data? i. [SELECT DISTINCT (repair) FROM parts_maintenance; and SELECT DISTINCT (reason) FROM parts_maintenance;] b. What are the benefits of using these queries to retrieve the information in a way that allows you to provide valuable information to your stakeholders? View data only from the fields you are interested in viewing. When you open a table, you see all the fields. Combine data from several data sources. A table usually only displays data that it stores. Use expressions as fields. View records that meet criteria that you specify. 4. Lastly, identify how the functions in the analysis tool allowed you to organize the data and retrieve records quickly so that they demonstrated what you wanted. a. Running the analysis tool, help quickly find the data we want, a combining the data to get total of information we are looking for. LIKE operator used in
conjunction with the WHERE clause matches text against a pattern using the two wildcard characters % and _.
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