Report on Using and Managing Data and Information in Microsoft Excel

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Added on  2023/06/08

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This report provides an overview of using and managing data and information in Microsoft Excel. It details the application of Excel for organizing, calculating, and manipulating data through formulas and spreadsheets. The report covers two main parts: Part A focuses on using the IF function to select employees based on specific criteria, demonstrating how to display 'yes' or 'no' based on conditions met in a survey. Part B explains how to calculate remaining holidays using subtraction, showing the calculation of employee vacation days over a six-month period. The conclusion emphasizes the importance of effective data handling for business operations and decision-making, highlighting the benefits of using Excel for various data-related tasks. The report also includes a list of references to support the information provided.
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Using and Managing
Data and information
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Contents
Contents...........................................................................................................................................2
INTRODUCTION...........................................................................................................................3
TASK 4............................................................................................................................................3
Part A...........................................................................................................................................4
Part B...........................................................................................................................................5
CONCLUSION................................................................................................................................5
REFERENCES................................................................................................................................6
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INTRODUCTION
Excel is a program which is present in the form of spreadsheet and is one of the part of
Microsoft excel. It aids users in the organizing, calculating and a set formulate which is used to
manipulate the data. In the prescribed report, it states about the employees whom have fallen in
the prescribed criteria will show as ‘yes’ and if not then it will show ‘no’. In the next part, it
states the remaining holidays of the employees which is calculated of the six-month period.
TASK 4
Ms-Excel utilizes or correlates information and conducts investigations based on the
information given. It is used to perform little to very large functions. The basic purposes of
success include:
Charting and graphing
Data entry
Time management
Customer relationship management (CRM)
Accounting
Anything that needs to be organized
Data Management
Programming
Ms-Excel is a programming that adjusts information using different surrogate abilities and
equations to improve understanding of information.
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Part A
Formula used : =IF(AND(B2>8,C2<2),"Yes","No")
In this section, it explains the selection of representatives according to the selection rules
specified in the survey. In the accompanying survey, that's assuming the worker has done it more
than 10 times and been ready for less than 2 days. It will show "yes" instead of the value in the
container if the possibility of the accompanying model is met, and "no" if it doesn't. First, select
the target cell where the result will be displayed. In this cell, he is above all the discoveries that
are applied to determine the recipe (Bifet and et.al., 2018).
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Part B
Formula used is subtraction as the remaining holiday has to calculate.
In this section, workers are eligible to claim 15 days of vacation every six months. The
equation is used to know the remaining leaves of the representation. The accompanying equation
is used to calculate the worker's remaining time. In the target cell, the recipe is used to determine
the balance of the remaining occasions (Ghani and et.al., 2019).
CONCLUSION
From the above report, it is crucial to handle the utilization of information and data in a
robust manner. Success can be thought of as a means of handling business association
information. Successfully used for different purposes, estimates can be made and organizations
can keep up with the vast amount of information that is obtained. As the association performs
different tasks and by utilizing the various sets of information in the success table, it can be well
monitored in a successful manner.
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REFERENCES
Books and Journals
Bifet, A. and et.al., 2018. Machine learning for data streams: with practical examples in MOA.
MIT press.
Ghani, N.A. and et.al., 2019. Social media big data analytics: A survey. Computers in Human
Behavior, 101, pp.417-428.
Gupta, A. and Nain, H., 2021. Bitcoin price prediction using time series analysis and machine
learning techniques. In Machine Learning for Predictive Analysis (pp. 551-560).
Springer, Singapore.
Kamble, S.S., Gunasekaran, A. and Sharma, R., 2020. Modeling the blockchain enabled
traceability in agriculture supply chain. International Journal of Information
Management, 52, p.101967.
Kovacova, M. and Lewis, E., 2021. Smart factory performance, cognitive automation, and
industrial big data analytics in sustainable manufacturing internet of things. Journal of
Self-Governance & Management Economics, 9(3).
Lu, Y. and Da Xu, L., 2018. Internet of Things (IoT) cybersecurity research: A review of current
research topics. IEEE Internet of Things Journal, 6(2), pp.2103-2115.
Pritchard, H.D., 2019. Asia’s shrinking glaciers protect large populations from drought
stress. Nature, 569(7758), pp.649-654.
Sajjad, M. and et.al., 2019. Multi-grade brain tumor classification using deep CNN with
extensive data augmentation. Journal of computational science, 30, pp.174-182.
Sundaram, S. and et.al., 2019. Learning the signatures of the human grasp using a scalable tactile
glove. Nature, 569(7758), pp.698-702.
Tao, F. and et.al., 2018. Digital twin in industry: State-of-the-art. IEEE Transactions on
industrial informatics, 15(4), pp.2405-2415.
Wan, S. and et.al., 2020. Deep learning models for real-time human activity recognition with
smartphones. Mobile Networks and Applications, 25(2), pp.743-755.
Xiao, F., 2019. Multi-sensor data fusion based on the belief divergence measure of evidences and
the belief entropy. Information Fusion, 46, pp.23-32.
Yaqoob, I. and et.al., 2019. Internet of things forensics: Recent advances, taxonomy,
requirements, and open challenges. Future Generation Computer Systems, 92, pp.265-
275.
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