Campbell CSIS325-D01
Introduction
In a digital age, there is an increasing need for responsibility for data integrity for
organizations to remain competitive. Data integrity is the accuracy, reliability, and consistency of
data throughout the data life cycle (Duggineni, 2023).
Markets for data quality tools are growing 16% annually (Fan & Geerts, 2022). Old
practices are merged with new technology to achieve new heights in performance, operational
excellence, and innovation through the use of big data, cloud computing, machine learning,
artificial intelligence, IoT-connected operations with devices (Santos et al., 2021). Reliable data
provides opportunities for an organization to expand into new and bigger markets, ultimately
contributing to growth of revenue.
Problem Statement
Without the reliability of data, decision making could make or break an organization.
Organizations might experience financial losses from decision errors that resulted from poor data
quality, reputational damage if inconsistencies are exposed, missed opportunities including
market trends, inefficiencies such as having problems with management of inventories, or legal
issues when the organization isn’t complying with security regulations (Pansara, 2023). A lot of
time, effort, and money goes into business decisions, performance assessments, critical and non-
critical inventories, and sales analytics.
Inaccurate documentation fails to represent real life in the way it is meant to. Human error,
glitches with the system, and outdated information affect data integrity (Pansara, 2023).
Incomplete documentation does not contain required elements or information that provides a full
picture which creates gaps in understanding that affect data-driven decisions (Pansara, 2023).
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Inconsistency presents discrepancies or contradictions that lead to errors in reporting, analysis,
and decision making (Pansara, 2023). Irrelevant information misaligns the needs of the
organization and objectives for its users (Pansara, 2023). Volume and velocity of data, data
integration, data governess (effective practices, quality standards, and constantly evolving
process), privacy and security, and human error are all pitfalls in good data documentation
(Pansara, 2023).
Errors might seem insignificant, but the problem can easily become magnified until they are
issues that affect current and future business.
Purpose Statement
This paper examines measures of improving the integrity of data through validation and
automation to ensure organizational uprightness in competitive markets. Giving careful
consideration to the potential dangers of poor data quality and its contributing factors, this paper
will explore good documentation practices and measures to ensure that integrity of data is
cultivated and maintained.
Literature Review
Measures to ensure data integrity include checksums, version controls, audit trails, and log
monitoring. Highly impactful practices that ensure data integrity throughout the data lifecycle
(Duggineni, 2022): Validating input before it is entered into the database, access controls or
permissions ensure that a limited number of people have access to updating critical information,
maintaining audit trails through an automatic monitoring system that identifies the origin of
changes once records are updated, periodic back up procedures carried out by trusted individuals,
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and education and formal training on the database- building a culture of effective data
management.
Data management practices aim to manage, centralize, localize, categorize, synchronize data
that aligns with organizational policies, procedures, and goals (Ronak, 2023). Sources of master
data could be the customer, products, stores, products, suppliers, employees, and digital assets
(Ronak, 2023). As the workplace is fast moving and changing, the leaders of the organization
need to be committed to solving problems of the near future before they occur (Santos et al.,
2021).
Creating and maintaining a workforce that is trained and highly skilled includes a dynamic
training system by up-skilling, re-skilling, continuous learning, and encouraging a mindset
change (Santos et al., 2021). The workforce should be willing to adopt organizational change,
acquiring new skills, learning new jobs or tasks, and retraining mid-career (Santos et al., 2021).
This can be attained through incentivizing training programs and encouraging leadership,
creativity, and innovation (Santos et al., 2021). Data governance refers to the exercise of
authority and control over the management of data (Abraham, Schneider, & vom Brocke, 2019).
The goal of D.G is to increase the value of data and mitigate data-related cost and risk (Abraham,
Schneider, & vom Brocke, 2019).
Biblical Application
Integrity has been a focus of discussion surrounding the followers of Christ. Doubts and
questions of Christian behaviors has come into question more frequently over the last few years
(Aladegbami, 2022). Integrity must be shown both in public and in private, and Christians are
encouraged to adopt the attitude of Christ as they walk on their journey with him. Honesty,
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morality and integrity are becoming less and less frequent, yet there is a growing need for this in
society. “It has been acknowledged that integrity is a "fundamental aspect of Christianity,
without which Christians cannot reflect light to others as Christ did (Aladegbami,2022). Proverbs
4: 25-27 says, “Let your eyes look straight ahead; fix your gaze directly before you. Give careful
thought to the paths of your feet and be steadfast in all your ways. Do not turn to the right or the
left; keep your foot from evil (The ESV study Bible: English standard version, 2008).” There is a
sense of duty and consciousness that a follower Christ should be connected to and understand the
will of God for their lives. Strong willingness and honesty must be practiced to continuously
seek and incorporate the word of God in their lives (Aladegbami,2022).
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Sources:
Abraham, R., Schneider, J., & vom Brocke, J. (2019). Data governance: A conceptual
framework, structured review, and research agenda. International Journal of Information
Management, 49(2), 424–438. https://doi.org/10.1016/j.ijinfomgt.2019.07.008
Aladegbami, O. (2022). Christian Attitude and Integrity [Review of Christian Attitude and
Integrity]. Nigerian Journal of Christian Studies, 4(2). African Journals Online.
file:///C:/Users/kleig/Downloads/ajol-file-
journals_598_articles_220872_submission_proof_220872-7035-541346-1-10-
20220204.pdf
Duggineni, S. (2023). Impact of Controls on Data Integrity and Information Systems [Review of
Impact of Controls on Data Integrity and Information Systems]. Science and Technology,
13(2), 29–35. https://doi.org/10.5923/j.scit.20231302.04
Fan, W., & Geerts, F. (2022). Foundations of Data Quality Management. Springer Nature.
Pansara, R. (2023). Cultivating Data Quality to Strategies, Challenges, and Impact on Decision-
Making [Review of Cultivating Data Quality to Strategies, Challenges, and Impact on
Decision-Making]. International Journal of Managment Education for Sustainable
Development, 6(6). https://ijsdcs.com/index.php/IJMESD/article/view/356/131
Ronak, Ravjibhai (2023). Master Data Management important for maintaining data accuracy,
completeness & consistency. TechRxiv. Preprint.
https://doi.org/10.36227/techrxiv.24053862.v1
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Santos, G., Sá, J. C., Félix, M. J., Barreto, L., Carvalho, F., Doiro, M., Zgodavová, K., &
Stefanović, M. (2021). New Needed Quality Management Skills for Quality Managers
4.0. Sustainability, 13(11), 6149. https://doi.org/10.3390/su13116149
The ESV study Bible: English standard version. (2008). Crossway Bibles.
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