DAD 220 Analysis and Summary Medeiros
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DAD 220 Analysis and Summary Template
Replace the bracketed text in this template with your responses and any supporting screenshots. Then
submit it to the Module Five Activity for grading and feedback. Rename this document by adding your
last name to the file name before you submit.
Explanation:
Created a table names
PartsMaintenance
using the following command:
CREATE TABLE PartsMaintenance (vehicle_id VARCHAR(20),
state VARCHAR(2), repair VARCHAR(50), reason VARCHAR(50),
year INT, make VARCHAR(20), body_type VARCHAR(50));
I was then able to show the command worked using the following
show table
command:
show tables;
1.
Analyze the data
you’ve been provided with to
identify themes
:
a.
Which parts are being replaced most?
Explanation:
Using the commands below:
SELECT repair AS PART_REPAIR, COUNT(*) AS NUMBER_OF_REPAIRS
FROM PartsMaintenance
GROUP BY PART_REPAIR
ORDER BY NUMBER_OF_REPAIRS DESC;
We can identify that the “
Fule” tank
(Fuel tank) is the most replaced part coming in at
95
replacements
.
b.
Is there a region of the country that experiences more part failures and replacements
than others?
i.
Identify region:
Explanation:
We can identify which region of the country that experiences more part failures and
replacements using the command below:
SELECT 'SOUTHWEST' AS REGION, COUNT(*) AS NUMBER_OF_REPAIRS
FROM PartsMaintenance
WHERE UPPER(state) IN ('AZ','NM','TX','OK')
UNION
SELECT 'NORTHEAST' AS REGION, COUNT(*) AS NUMBER_OF_REPAIRS
FROM PartsMaintenance
WHERE UPPER(state) IN ('PA','NJ','NY','CT','RI','MA','VT','ME','NH')
UNION
SELECT 'SOUTHEAST' AS REGION, COUNT(*) AS NUMBER_OF_REPAIRS
FROM PartsMaintenance
WHERE UPPER(state) IN ('AR','LA','AL','GA','TN','SC','NC','VA','WV','DE','MD')
UNION
SELECT 'MIDWEST' AS REGION, COUNT(*) AS NUMBER_OF_REPAIRS
FROM PartsMaintenance
WHERE UPPER(state) IN ('ND','SD','KS','NE','MN','WI','IA','MO','MI','IN','IL','OH')
UNION
SELECT 'WEST' AS REGION, COUNT(*) AS NUMBER_OF_REPAIRS
FROM PartsMaintenance
WHERE UPPER(state) IN ('WA','ID','MT','OR','WY','CO','UT','NV','CA')
ORDER BY NUMBER_OF_REPAIRS DESC;
The result of this query identifies the
Midwest
as experiencing the most part failures with
260
repairs
while the nest closest region is the
Northeast
with
208 repairs.
Using the
UNION
command to combine the multiple results that were received from
each
SELECT
statement that represented their own specific region.
ii.
How might the fleet maintenance team use the information to update its
maintenance schedule?
1.
Fleet Maintenance can use this information to alter their maintenance
schedule.
2.
More resources can be allotted to the regions with the highest number
of repairs.
3.
The team can from this point schedule and do more preventative
maintenance in those higher regions.
4.
Combining the previous tables with this information can also allow the
inventory and logistics departments to use more warehouse space for
the more pertinent parts that are needed.
c.
Which parts are being replaced most due to corrosion or rust?
i.
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Explanation:
Using the below command allows us to see which parts are being replaced most due to
corrosion or rust:
SELECT repair AS PART_REPAIR,COUNT(*)
AS NUMBER_OF_REPAIRS FROM PartsMaintenance
WHERE UPPER(reason) IN ('CORROSION','RUST')
GROUP BY PART_REPAIR
ORDER BY NUMBER_OF_REPAIRS
DESC;
Using the above code to disseminate the information that we need.
We can clearly see that
Wheel
Arch
and
Fender replacement
are the top 2 parts that are replaced due to rust or corrosion.
The
maintenance team can use this information as part of a preventative maintenance plan.
d.
Which parts are being replaced most because of mechanical failure or accident, like a
flat tire or rock through the windshield?
i.
Explanation:
We can retrieve the information on which parts are being replaced most because of
mechanical failure or accident (flat tire or rock through the windshield)
using the command below:
SELECT repair AS PART_REPAIR,COUNT(*)
AS NUMBER_OF_REPAIRS FROM PartsMaintenance
WHERE UPPER(reason) LIKE '%FLAT%' OR
UPPER(reason) LIKE '%CRACK%'
GROUP BY PART_REPAIR
ORDER BY NUMBER_OF_REPAIRS DESC;
The result of this query shows us the parts that are being replaced most because of mechanical failure or
accident (flat tire or rock through the windshield) are
Tires
.
Having this information readily accessible to
the maintenance team will allow them to keep the needed tires in stock, and make sure that every
vehicle has the tools/equipment to deal with slow leaks or blow outs.
2.
Write a brief summary of your analysis
that
takes the information from Step 1 and presents it in
a way that nontechnical stakeholders can understand.
a.
With the data that we retrieved from Step 1 there are some important trends to pay
special attention to the “
Fule Tank”
(Fuel Tank) to get down to the reason why it is the
most replaced part.
On top of the issue with the “
Fule Tank”
(Fuel Tank), the “
Midwest”
has the highest number of part failures, which is a cause for a diversion of resources
from the areas that don’t need as much resources as the rest of the areas (think of a
tiered resource system) to fortify the Midwest.
In closing, using this data and applying it
to the fortification of resources in the Midwest and the replacement of Wheel Arch and
Fenders due to rust and corrosion and prioritize preventative measures for these 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?
SELECT repair AS PART_REPAIR, COUNT(*) AS NUMBER_OF_REPAIRS
FROM PartsMaintenance
GROUP BY PART_REPAIR
ORDER BY NUMBER_OF_REPAIRS DESC;
This was the first query we ran that allowed us to identify the most replaced part in the
entire fleet.
SELECT 'SOUTHWEST' AS REGION, COUNT(*) AS NUMBER_OF_REPAIRS
FROM PartsMaintenance
WHERE UPPER(state) IN ('AZ','NM','TX','OK')
UNION
SELECT 'NORTHEAST' AS REGION, COUNT(*) AS NUMBER_OF_REPAIRS
FROM PartsMaintenance
WHERE UPPER(state) IN ('PA','NJ','NY','CT','RI','MA','VT','ME','NH')
UNION
SELECT 'SOUTHEAST' AS REGION, COUNT(*) AS NUMBER_OF_REPAIRS
FROM PartsMaintenance
WHERE UPPER(state) IN ('AR','LA','AL','GA','TN','SC','NC','VA','WV','DE','MD')
UNION
SELECT 'MIDWEST' AS REGION, COUNT(*) AS NUMBER_OF_REPAIRS
FROM PartsMaintenance
WHERE UPPER(state) IN ('ND','SD','KS','NE','MN','WI','IA','MO','MI','IN','IL','OH')
UNION
SELECT 'WEST' AS REGION, COUNT(*) AS NUMBER_OF_REPAIRS
FROM PartsMaintenance
WHERE UPPER(state) IN ('WA','ID','MT','OR','WY','CO','UT','NV','CA')
ORDER BY NUMBER_OF_REPAIRS DESC;
This was the second query that we ran that allowed us to split the entire country up into
regions and identify which region had the most part failures and it returned that the Midwest
was experiencing the most part failures.
By using the
UNION
command to combine the multiple
results that were received from each
SELECT
statement that represented their own specific
region.
SELECT repair AS PART_REPAIR,COUNT(*)
AS NUMBER_OF_REPAIRS FROM PartsMaintenance
WHERE UPPER(reason) IN ('CORROSION','RUST')
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GROUP BY PART_REPAIR
ORDER BY NUMBER_OF_REPAIRS
DESC;
This was our third query and it allowed us to see what parts were the most replaced due
to damage caused by rust or corrosion.
The
“WHERE”
clause in the statement acts as the filter
for the data and is based on specified reasons such as
“RUST”
and/or
“CORROSION”
in the
“
Reason”
column of the table.
“COUNT”
calculates the number of parts replacements, using the
combination of these commands in the coding allows us to identify the parts that are the most
susceptible to rust or corrosion related issues.
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?
i.
These queries are beneficial and provide insights to the stakeholders
because they help to identify the most replaced parts, doing so allows feet
maintenance to prioritize and institute preventative measures on the parts that
need extra attention.
These queries also break the country down to regions and doing so
allows the company to analyze the regions differently and “rank” them I n terms
of a “worst to first” method that would allow some resources to be diverted
from the lesser needed areas to the “worst” or “most needed” areas.
They also
can prevent much of the damage done by rust and corrosion.
The company can also identify most parts replaced due to mechanical
failures or accidents which will allow them to take measures targeted at either
preventing these incidents or limiting them and improving the overall safety and
effectiveness of the fleet.
When the effectiveness of the fleet is improved and
more reliable it allows us to offer a more efficient service to everyone, including
the stakeholders.
4.
Explain how the functions in the analysis tool
allowed you to organize the data and retrieve
records quickly.
a.
The functions in the analysis tool helped greatly in the organization of the data and
quickly retrieving records.
This allowed our process of analysis to be quick and efficient.
“SELECT” --
Allowed me to apply specification to the data that needed to be retrieved.
(Part name, # of replacements…. etc.) this made the results clear, relevant, and easy to
read/understand.
“GROUP BY” –
Allowed the grouping of data based on part names, this made it easy to
identify the most replaced parts and overall impact on the fleet.
“COUNT” –
Allowed me to calculate the total number of replacements for each part.
Having this knowledge makes it easy to know what you want to prioritize and direct
resources.
“ORDER BY” –
Allowed me to sort the data in either ascending or descending order.
Being able to use this command made it easy when I needed to identify the parts that
had the highest replacement counts.
“UNION” –
Allowed us to combine data from multiple queries.
Using this function
helped with returning relevant and accurate records quickly.
By using these functions, it helped me to get a better understanding of parts
patterns and gave me the data to make data-driven decisions and formulate a plan to
enhance the fleet’s reliability and safety.
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