Data Analytics for Business: Extracting, Cleaning, and Analyzing Data in the Airline Industry

This article discusses data analytics for business in the airline industry, including extracting and cleaning data, summary statistics, and common reasons for delays. It also provides recommendations for business owners and passengers to improve customer satisfaction and loyalty.

DATA ANALYTIC FOR BUSINESS

TABLE OF CONTENTS
Extracting data ........................................................................................................................................................................................3
Cleaning and transforming the data ........................................................................................................................................................3
Summary statistics...................................................................................................................................................................................3
Summarizing the business problems and determine data to be used for analysis...................................................................................6
Presenting common reasons for delays within airline industry...............................................................................................................7
Recommendations for business owners and passengers..........................................................................................................................7
REFERENCES............................................................................................................................................................................................8

Extracting data
Extracting data is a process that involve storing the information that is relevant and essential in respect to the topic of study.
Sources are identified and based on that information is collected under this process (ALI and et.al., 2021). The role of extracting data
is to segregate the relevant information and process all the information in the most useful way possible. When it comes to delivering
research data and information is the core area and the method to deliver the entire study. The role of the extracting data is about to
deliver the overall research conducted.
Cleaning and transforming the data
In order to clean and extract the data, different steps have been used which are as mentioned below:

Step 1: Apply filters in entire first row, this helps to select the data which actually needed.

Step 2: By clicking on filter, select blank spaces in order to delete the same for cleaning the data.

Step 3: Delete the selected rows identified in the above step

Step 4: Proceed with the available data in order to generate the descriptive statistics.
Summary statistics
SCHED
ULED_
DEPAR
TURE
DEPA
RTUR
E_TI
ME
DEPA
RTUR
E_DEL
AY
TA
XI
_O
UT
WH
EEL
S_O
FF
S
C
H
E
D
U
L
E
D
_
ELAPSED
_TIME
DISTA
NCE
W
HE
EL
S_
O
N
TA
XI_
IN
SCHE
DULE
D_AR
RIVA
L
ARRI
VAL_
TIME
ARRI
VAL_
DEL
AY
DI
VE
RT
ED
CA
NC
ELL
ED

T
I
M
E
Mean 1326.326
1333.
022
9.6572
16
16.
115
96
1354
.782
1
4
2
.
4
3
9 137.6876
830.49
27
14
67.
06
2
7.55
314
1
1483.9
3
1469.5
35
4.905
772 0 0
Stand
ard
Error 6.368746
6.554
089
0.4728
1
0.1
195
56
6.57
4052
0
.
9
9
0
1
6
7 0.975962
8.0502
97
6.8
71
88
8
0.07
544
1
6.6907
94
6.9421
15
0.509
736 0 0
Medi
an 1325 1330 -1 14 1342
1
2
3 119 647
15
04 6 1515 1507 -5 0 0
Mod
e 600 655 -3 11 715
8
5 82 337
12
48 4 2100 1906 -6 0 0
Stand
ard
Devi
ation 488.7779
503.0
023
36.286
46
9.1
755
01
504.
5344
7
5
.
9
9
1
6
8 74.90153
617.83
08
52
7.3
92
2
5.78
980
1
513.49
39
532.78
19
39.12
04 0 0

Samp
le
Varia
nce 238903.8
25301
1.3
1316.7
07
84.
189
81
2545
54.9
5
7
7
4
.
7
3
6 5610.239
381714
.9
27
81
42.
6
33.5
218
26367
6
28385
6.5
1530.
406 0 0
Kurt
osis -1.00002
-
0.974
9
67.603
41
28.
127
87
-
0.91
908
2
.
0
3
9
2
6
1 2.152837
2.5609
47
-
0.5
59
04
40.1
726
5
-
0.5456
1
-
0.4623
4
52.64
024
#DI
V/
0!
#DI
V/0!
Skew
ness 0.048198
0.005
669
6.1860
46
3.8
287
72
-
0.02
797
1
.
3
6
2
9
0
9 1.375128
1.4630
65
-
0.2
85
14
4.66
909
8
-
0.2711
3
-
0.3319
9
5.317
427
#DI
V/
0!
#DI
V/0!
Rang
e 2349 2355 723 143 2358
5
8
2 582 4916
23
99 94 2358 2399 740 0 0
Mini
mum 10 4 -25 3 1
3
2 30 67 1 1 1 1 -60 0 0
Maxi
mum 2359 2359 698 146 2359
6
1
4 612 4983
24
00 95 2359 2400 680 0 0
Sum 7812061 78515 56881 949 7979 8 810980 489160 86 444 87403 86555 28895 0 0

02 23 665
3
8
9
6
6 2
40
99
4 88 47 62
Coun
t 5890 5890 5890
589
0 5890
5
8
9
0 5890 5890
58
90
589
0 5890 5890 5890
589
0
589
0
Interpretation:
Trend:
Through the above table, it has been examined that average arrival time of the selected airlines are high as compared to the
departure time. That is why, it can be stated that average number of arrival delay time taken by the airplanes are less as compared to
departure. Thus, it can be stated regard to trend that companies must focused upon the departure time because there are many flights
who got delayed due to many reasons. Apart from this, minimum 32 minutes are taken by the airplanes regarding to their schedule
time which in turn assist to determine that airplanes take off at time that helps to maintain the customer satisfaction level. Overall, it
can be stated that arrival time is more effective as compared to departure time and by focusing upon the same, it will generate the best
outcomes too.
Summarizing the business problems and determine data to be used for analysis
There are many issues that has been a part of the research conducted over the given topic. The time-consuming process in
order to identify various information has been one of the core issue associated with the study conducted. The time taken was the major
challenge that is associated with the study conducted by the scholar (Bakir and et.al., 2020). This is about to ensure the best form of
information collection in against to deliver the research study. The authenticity of the sources identified is another key issue part of the

study conducted. This is essential for the business that is also highlighted under the study conducted. The external business
environment is also a key issue or the challenge thaty involve in the business functions conducted. In context to the airline sector
services are multiple that is catered to the customers in market that also become a huge challenge for the business houses.
Presenting common reasons for delays within airline industry.
There are certain common delays associated with the airline business. The reason behind the delay is that there are many
services that airline business houses delegate that support the customer satisfaction in the best way possible. Also many times due to
poor weather condition the delay occur in the business operations of company. Along with this many times the technical errors also
become the reason of delay in the practices conducted by the airline sector organization. Many situations also arises where due to
usual circumstances delay is occur in delivering services at the organization. There are many situations that are completely
unavoidable in nature that become a reason of the delay in the services.
Recommendations for business owners and passengers
 This is recommended that timings can get more flexible in the time of poor weather conditions.
 This is recommended that the company can coconut timely basis of maintenance activities so that proper support can delegate
to the business operations conducted at the organization (Gibson and Mourad, 2018).
 This is also recommended that the organization should also ex[and its service areas so that more growth opportunists could
have been delivered to the business house.

REFERENCES
Books and Journals
ALI, J. and et.al., 2021. Service Quality and Its Impact on Customer Satisfaction and Loyalty in Airline Industry: Partial Least Square
(PLS)-Structural Equation Modelling (SEM) Approach.
Journal of Contemporary Issues in Business and Government. 27(3).
pp.2212-2224.
Bakir, M. and et.al., 2020. Multiple-criteria approach of the operational performance evaluation in the airline industry: Evidence from
the emerging markets.
Rom. J. Econ. Forecast. 23. p.149.
Gibson, P. and Mourad, T., 2018. The growing importance of data literacy in life science education.
American journal of
botany. 105(12).