Data Collection and Quality Assessment

Data Collection and Quality Assessment

Data governance is the process or system of monitoring and determining access and control of an organization’s data assets. The quality and appropriateness of the data held by an organization is a significant aspect of data governance. Data collection and quality assessment in data governance entails various steps. The steps for data collection include identifying the data to be collected, time to be spent on data collection, method(s) of data collection, and data collection and analysis. For data quality analysis, data definition, assessment, analysis, implementation, and control are performed (Hassenstein & Vanella, 2022). To identify the data to be collected, the purpose of data collection must be defined. The duration of data collection should be set. This would be determined by the amount of data collected and the ongoing business operations. That data would then be analyzed. Data analysis would begin by selecting the expected quality of data (Hassenstein & Vanella, 2022). That is the accepted data value. Data assessment would then be performed based on the definition made in step one. After data assessment, data analysis would be done to identify any inconsistencies. If inconsistencies are observed, they will be rectified before implementation, and controls will be placed to ensure such discrepancies do not occur in the future.

Data collection within an organization for data governance purposes; the data in the database could be assessed based on the expected data format and values. An IT team could do this to ensure that different data files and reports are considered. Examples of data that would be evaluated would include customer names, addresses, contact information, financial statements, sales reports, etc. Misspelled words, incomplete or missing addresses, contact information, and preliminary descriptions would be considered data inconsistencies requiring correction. The IT team consists of data quality analysts (s), data entry officers, database administrators, and system security. Data entry officers would facilitate inconsistency corrections by entering test data to check if the data controls implemented work as expected. The database administrator would provide information on how to pull data from the various database tables and help to identify structural issues that could lead to data inconsistencies. IT system security would ensure the system is secure during data collection and correction of data inconsistencies.

Some security risks associated with data collection include illegal access to data, denial of service attacks, and introducing of malicious programs into the system (Cobb et al., 2018). Attackers could exploit the data collection process by gaining unauthorized access to data. They could also inject SQL codes to use the database or attack network hosts to cause a denial of service attack.

References

Cobb, C., Sudar, S., Reiter, N., Anderson, R., Roesner, F., & Kohno, T. (2018). Computer security for data collection technologies. Development Engineering, 3, 1-11. https://www.sciencedirect.com/science/article/pii/S2352728516300677

Hassenstein, M. J., & Vanella, P. (2022). Data Quality—Concepts and Problems. Encyclopedia, 2, 498–510. https://www.mdpi.com/2673-8392/2/1/32/pdf

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Data Collection and Quality Assessment

Imagine that you must collect and assess the quality and appropriateness of data held by a large multinational organization. What steps would you take? Include how you would address network, security, and ethical considerations when deciding what data to collect from the company. Explain the kinds of support you will need and how you will obtain resources and cooperation.