Using and Managing Data and Information

This report provides detailed information about managing data. It includes calculation of moving average and centre moving average, tree diagram and linear programming. The report also provides different calculation off codes for different categories and it also represents different frequencies of gender education age spending and SCC user.

Using and Managing Data and
Information

Table of Contents
Introduction......................................................................................................................................4
TASK 1............................................................................................................................................4
1. Label the codes for categories...........................................................................................4
2...................................................................................................................................................4
Gender..........................................................................................................................................4
Education.....................................................................................................................................5
Age...............................................................................................................................................5
SCC user......................................................................................................................................5
Spending......................................................................................................................................6
3.......................................................................................................................................................6
Education.....................................................................................................................................6
Age...............................................................................................................................................6
Spending......................................................................................................................................7
TASK 3............................................................................................................................................8
2. Calculation of moving average................................................................................................8
3. Centre moving average............................................................................................................9
Centre moving average................................................................................................................9
TASK 4..........................................................................................................................................10
Tree diagram to represent the probabilities of being selected a salesperson.............................10
TASK 5..........................................................................................................................................11
Using linear programming solving the problems......................................................................11
Conclusion.....................................................................................................................................13

References........................................................................................................................................1

Introduction
The entire report focuses on using and managing data and information (Nawab and et.al 2018). It
is very important to manage data in appropriate manner so that it can produce more reliable and
accurate information to the user. This report provides different calculation off codes for different
categories and it also represents different frequencies of gender education age spending and SCC
user.
TASK 1
1. Label the codes for categories
Customer Gender Age Education SSC user
1 Male 35 to 47 A' level or
diploma
Yes
2 Female 61 and over Degree or further No
3 Female 35 to 47 GCSE or below Yes
4 Female 61 and over GCSE or below No
5 Female 48 to 60 Degree or further No
Interpretation: After analysing the entire chat it has been interpreted that male are user of SSC
on the other hand most of the female who are above 60 years of age they are not user of SSC
apart from this does female who are below 47 years but above 35 years they are also user of SSC
and apart from this dose female who are above 48 years they are not so much user of SSC
(Pecheux, and et.al 2020).
2.
Gender
Particulars Frequency
%
frequenc
y
Male 20 40%
Female 30 60%
Grand Total 50 100%

From the above table it has been interpreted that 60% are female and 40% are male
Education
Particulars Frequency
%
frequency
GCSE or
below 20 40%
A’ Level or
Diploma 16 32%
Degree or
further 14 28%
Grand Total 50 100%
In the education 40% are GCSE and below 32% are a level or diploma and 28% are having
degree.
Age
Particulars Frequency
%
frequency
Less than 21 2 4%
21 to 34 5 10%
35 to 47 10 20%
48 to 60 26 52%
61 and over 7 14%
Grand Total 50 100%
From the above table it has been interpreted that 4% have less than 21 to 34 ,10 % are between
35 to 47 , 20 % are 35 to 47 and 52% fall under 48 to 60 and 14% are 61 and above (Oh and et.al
2019).
SCC user
Particulars Frequency
%
frequenc
y
Yes 17 34%
No 33 66%
Grand Total 50 100%
34% people are SCC user but 66% people do not use.

Spending
Particulars Frequency
%
frequency
<100 1 10%
100-109 6 12%
110-119 23 46%
120-129 18 36%
130-140 2 4%
>140 0 0%
Grand Total 50 100%
From the above table it has been interpreted that 10% are below than hundred. On the other hand
12% are between 100 to 109Apart from this 46% are between 110 to 119. So the highest is 46%
falls under 110 to 119 (Lenzerini, 2018).
3.
Education
GCSE or below; 20
A’ Level or Diploma; 16
Degree or further ; 14
Age

Less than 21
21 to 34
35 to 47
48 to 60
61 and over
0 5 10 15 20 25 30
Age
Spending
<100 100-109 110-119 120-129 130-140 >140
0
5
10
15
20
25
Spending
Frequency
4.

Particulars Spending (£)
Mean 117.5
Minimum 92
Maximum 131
Median 118.5
Quartile 1 112
Quartile 2 118.5
Quartile 3 122.25
TASK 3
Year Quarter Sales
2017
1 139
2 135
3 91
4 113
2018
1 145
2 137
3 85
4 118
2019
1 150
2 141
3 89
4 119
2020
1 156
2 149
3 105
4 125
2. Calculation of moving average
Year Quarter Sales Moving average
2017 1 139 -
2 135 -

3 91 -
4 113 121.6667
2018
1 145 113
2 137 116.3333
3 85 131.6667
4 118 122.3333
2019
1 150 113.3333
2 141 117.6667
3 89 136.3333
4 119 126.6667
2020
1 156 116.3333
2 149 121.3333
3 105 141.3333
4 125 136.6667
3. Centre moving average
Year Quarter Centre moving average
2017
1
2 118.5
3 110
4 127
2018
1 128
2 119.25
3 109.5
4 131.75
2019
1 132.5
2 122.5
3 113.25
4 135.75
2020
1 141.5
2 132
3 83.75
4 62.5

TASK 4
Tree diagram to represent the probabilities of being selected a salesperson
Let A = Toni
B = Joe
 The probability of Toni to choose a salesperson = P(A) = 0.5
 The probability of Joe to choose a salesperson = P(B) = 0.4
 P (Salesperson chosen by both) = P (A and B) = 0 (as only one manager works in a day)
 P (A OR B) = P (A) + P (B) – P (A and B)
 = 0.5 + 0.4 – 0 = 0.8
Hence, this reflected that probability of a salesperson selected by either manager Toni and Joe is 0.8

0.3 + 0.16 = 0.46, it means the probability of selecting the employee is 46%
0.3 + 0.24 = 0.54, it means that the probability of not selecting the employee is 54%
0.3 + 0.3 + 0.16 + 0.24 = 1
TASK 5
Using linear programming solving the problems
Decision

variables
Objective
functions
LHS
constrains
Brie Goude
Total
Profit
Production
quantity 12 0
Unit profits 4.5 3 54
Constrain
ts
Production
Requirements
per Unit Used
Availab
le
Milk 1.8 1.2 21.6 120
Salt 100 150 1200 1200
Solver
Options
Max Time Unlimited, Iterations Unlimited,
Precision 0.000001
Max Subproblems Unlimited, Max Integer Sols Unlimited, Integer Tolerance
1%, Assume NonNegative
Objective Cell (Max)
Cell Name
Original
Value
Final
Value
$E$
4
Unit profits Total
Profit 54 54
Variable Cells
Cell Name
Original
Value
Final
Value Integer
$C$3 Production quantity 12 12 Contai

Brie n
$D$3
Production quantity
Goude 0 0
Contai
n
Constraints
Cell Name
Cell
Value Formula Status Slack
$E$7
Milk
Used 21.6 $E$7<=$F$7
Not
Binding 98.4
$E$8
Salt
Used 1200 $E$8<=$F$8 Binding 0
Conclusion
After analysing the entire report has been concluded that this report provides detailed
information about managing data. This report provides detailed information about calculation of
moving average and centre moving average. Along with this tree diagram has also been
mentioned in this report apart from this linear programming has been defined in this particular
report.

References
Books and Journal
Lenzerini, M., 2018. Managing data through the lens of an ontology. AI Magazine. 39(2).pp.65-
74.
Oh, S.L. and Rieh, H.Y., 2019. Managing data set in administrative information systems as
records. Journal of Korean Society of Archives and Records Management.19(2).pp.51-
76.
Pecheux, K.K., Pecheux, B.B., Ledbetter, G. and Lambert, C., 2020. Guidebook for Managing
Data from Emerging Technologies for Transportation (No. Project 08-116).
Nawab, F., Agrawal, D. and El Abbadi, A., 2018, May. Dpaxos: Managing data closer to users
for low-latency and mobile applications. In Proceedings of the 2018 International
Conference on Management of Data (pp. 1221-1236).
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