Exploring and Ensuring Data Quality in Consumer Electronics with Big Data Techniques

Registration ID: IJNRD_226642

Published ID: IJNRD2208186

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SHREYAS MAHIMKAR, ER. PRIYANSHI, PROF.(DR) SANGEET VASHISHTHA

• Data Quality • Consumer Electronics • Big Data Techniques • Data Cleaning • Data Validation • Advanced Analytics • Machine Learning • Data Warehousing • Anomaly Detection • Survey Data • Data Governance • Real-Time Analytics • Data Inaccuracies • Data Completeness • Artificial Intelligence

In the rapidly evolving field of consumer electronics, ensuring high data quality is paramount for driving innovation, enhancing user experiences, and maintaining competitive advantage. This paper explores the application of big data techniques to address and improve data quality issues within the consumer electronics industry. As the volume, variety, and velocity of data generated by modern electronic devices increase, so too do the challenges associated with maintaining accurate, reliable, and usable data. This research aims to investigate how big data methodologies can be leveraged to enhance data quality and proposes strategies for implementing these techniques effectively. The study begins with a comprehensive review of existing literature on data quality challenges specific to consumer electronics By integrating big data techniques such as data cleaning, validation, and advanced analytics, the research aims to provide solutions to these challenges. To empirically validate the effectiveness of these techniques, the research incorporates survey data from industry stakeholders, including data engineers, product managers, and consumers. The survey explores their perceptions of current data quality practices, the impact of data quality issues on their operations, and their experiences with big data solutions. The survey results offer valuable insights into the practical implications of data quality management and the perceived benefits and limitations of big data techniques. Key findings indicate that big data techniques, including machine learning algorithms, data warehousing, and real-time analytics, significantly enhance data quality by automating data validation processes, detecting anomalies, and providing actionable insights. The research concludes with recommendations for consumer electronics companies to adopt a holistic approach to data quality management, combining technological solutions with robust data governance practices. Emphasis is placed on the importance of ongoing training for staff, investment in advanced analytics tools, and the development of comprehensive data quality frameworks.

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SHREYAS MAHIMKAR, ER. PRIYANSHI, & PROF.(DR) SANGEET VASHISHTHA (August-2022). Exploring and Ensuring Data Quality in Consumer Electronics with Big Data Techniques. INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT, 7(8), 22-37. https://ijnrd.org/papers/IJNRD2208186.pdf

Volume 7 Issue 8, August-2022

Pages : 22-37

Paper Reg. ID: IJNRD_226642

Published Paper Id: IJNRD2208186

Downloads: 000121995

Research Area: Engineering

Author Type: Indian Author

Country: -, -, India

Published Paper PDF: https://ijnrd.org/papers/IJNRD2208186.pdf

Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2208186

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