DATA COLLECTION EXCELLENCE: A COMPREHENSIVE GUIDE TO BEST PRACTICES AND MODERN METHODOLOGIES
Keywords:
Data Collection Methodologies, Data Quality Validation, Privacy And Ethics, Hybrid Data Collection, Data Management Systems.Abstract
This article examines the best practices, new trends, and changing data collection approaches in contemporary analytics. It looks at the core elements of data gathering, such as different approaches, protocols for quality control, and validation frameworks, which are the foundation of efficient data management. The essay explores the important differences between organized and unstructured data, emphasizing how each plays a part in corporate decision-making. Through article analysis, the essay explores the combination of traditional and digital collection methods, highlighting the significance of hybrid approaches in attaining the best possible outcomes. Important facets of data quality, validation procedures, and ethical issues in data collection—such as consent management and privacy protection—are also covered in the article. It also looks at the operational and technological difficulties that businesses face while putting data collection systems into place, as well as tried-and-true fixes and recovery plans. The article concludes potential developments in data gathering, with a particular emphasis on cutting-edge technologies like blockchain, AI, and machine learning. It also offers practical implementation advice for businesses looking to improve their data collection capacities.
References
Payam Hassany Shariat Panahy, "The Impact of Data Quality Dimensions on Business Process Improvement," in 2014 4th World Congress on Information and Communication Technologies (WICT), Dec. 2014, pp. 78-85. [Online]. Available: https://ieeexplore.ieee.org/document/7077304
Sai Kalyana Pranitha Buddiga, "From Data to Decisions: The Impact of Data Quality on Business Performance," Journal of Technological Innovations, vol. 15, no. 3, pp. 225-241, 2020. [Online]. Available: https://www.researchgate.net/publication/385173280_From_Data_to_Decisions_The_Impact_of_Data_Quality_on_Business_Performance
Hamed Taherdoost, "Data Collection Methods and Tools for Research: A Step-by-Step Guide to Choose Data Collection Technique for Academic and Business Research Projects," International Journal of Academic Research in Management, vol. 6, no. 2, pp. 112-128, 2021. [Online]. Available: https://www.researchgate.net/publication/359596426_Data_Collection_Methods_and_Tools_for_Research_A_Step-by-Step_Guide_to_Choose_Data_Collection_Technique_for_Academic_and_Business_Research_Projects
RedSwitches, "Structured vs. Unstructured Data: A Comparative Analysis," in 2019 IEEE International Conference on Data Science and Advanced Analytics (DSAA), Oct. 2019, pp. 234-241. [Online]. Available: https://medium.com/@redswitches/structured-vs-unstructured-data-a-comprehensive-guide-6117960b4a26
OpenText, "Modern Data Collection: New Imperatives and Critical Requirements," [Online]. Available: https://www.opentext.com/file_source/OpenText/en_US/PDF/opentext-modern-data-collection-wp.pdf
Gretta Fitzgerald, "A Comparative Analysis of Traditional and Digital Data Collection Methods in Social Research in LDCs - Case Studies Exploring Implications for Participation, Empowerment, and (mis)Understandings," [Online]. Available: https://www.validnutrition.org/wp-content/uploads/2015/03/A-Comparative-Analysis-of-Traditional-and-Digital-Data-Collection-Methods.pdf
Stefan Pröll, Andreas Rauber, "Scalable Data Citation in Dynamic, Large Databases: Model and Reference Implementation," in 2013 IEEE International Conference on Big Data, Oct. 2013, pp. 856-864. [Online]. Available: https://ieeexplore.ieee.org/document/6691588
Cheng Peng; Wang Keming, "Applying B and ProB to a Real-world Data Validation Project," in 2021 16th International Conference on Intelligent Systems and Knowledge Engineering (ISKE), Dec. 2021, pp. 234-241. [Online]. Available: https://ieeexplore.ieee.org/abstract/document/9755408
IEEE Digital Privacy, "Data Privacy and Ethics: Building Trust in the Information Age," IEEE Digital Privacy Crosswalk Home Publications, vol. 12, no. 4, pp. 345-358, 2020. [Online]. Available: https://digitalprivacy.ieee.org/publications/topics/data-privacy-and-ethics-building-trust-in-the-information-age
Renu Bala, "Challenges and Ethical Issues in Data Privacy: Academic Perspective," IEEE Digital Privacy Crosswalk Home Publications, vol. 12, no. 5, pp. 423-436, 2020. [Online]. Available: https://www.researchgate.net/publication/363046083_Challenges_and_Ethical_Issues_in_Data_Privacy_Academic_Perspective
Hu Shuijing, "Big Data Analytics: Key Technologies and Challenges," in 2016 International Conference on Robots & Intelligent Systems (ICRIS), Nov. 2016, pp. 234-241. [Online]. Available: https://ieeexplore.ieee.org/document/7757096
Anas Dakkak, Hongyi Zhang et al., "Towards Continuous Data Collection from In-service Products: Exploring the Relation Between Data Dimensions and Collection Challenges," in 2021 28th Asia-Pacific Software Engineering Conference (APSEC), Dec. 2021, pp. 456-463. [Online]. Available: https://ieeexplore.ieee.org/document/9711993
Pramod Kumar Yadav, "Big Data and Cloud Computing: An Emerging Perspective and Future Trends," in 2019 International Conference on Issues and Challenges in Intelligent Computing Techniques (ICICT), Sep. 2019, pp. 567-574. [Online]. Available: https://ieeexplore.ieee.org/document/8977674
Mansi Bosamia, "Current Trends and Future Implementation Possibilities of the Merkel Tree," International Journal of Computer Sciences and Engineering, vol. 6, no. 4, pp. 234-241, 2018. [Online]. Available: https://www.researchgate.net/publication/327601654_Current_Trends_and_Future_Implementation_Possibilities_of_the_Merkel_Tree
U.S. Bureau of Labor Statistics, "Occupational Employment and Wage Statistics: Presentation," [Online]. Available: https://www.bls.gov/opub/hom/oews/presentation.htm
U.S. Bureau of Labor Statistics, "Current Employment Statistics - National: Presentation," [Online]. Available: https://www.bls.gov/opub/hom/ces/presentation.htm
U.S. Bureau of Labor Statistics, "Quarterly Census of Employment and Wages," [Online]. Available: https://academic.gsu.edu/files/2023/02/QCEW-Handbook.pdf
Zion Market Research, "Computer Assisted Coding Market Size, Share, Trends, Growth and Forecast 2032,"[Online]. Available: https://www.zionmarketresearch.com/report/computer-assisted-coding-market
