• Dr. Arun Kumar Marandi

Increased data relevance should lead to increased knowledge and responsiveness to the requirement for high-quality data solutions for supply chain management. Decision outcomes based on low quality data might be expensive. Supply chain managers should begin to look at the quality of the data products, on the basis of which the quality of the products supplied by their supply chain is taken into account for decision making. The goal of this study is the evaluation and synthesis of existing research relating to the use in healthcare engineering systems of data analytics, large data and data mining. This study seeks to present and highlight the requirement in supply chain management procedures for monitoring and monitoring data quality and to give a starting point for future research and applications. The article opens with a brief description of the process of data creation. The data quality is then described and the dimensions defined. This research next examines techniques for monitoring, managing and enhancing data quality and provides a practical example of how one business uses this strategy in the supply chain to improve data quality. This study then examines how the problem of data quality may be seen via systems theory, knowledge-based insight and information management in order to give guidance to future research through a number of theoretically-based themes. Finally, this study covers both management implications and further research.

Big Data, Data Quality, Data Science, Decision, Information.

"Data Science or Predictive Analytics Requirements", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 3, page no.74-79, March-2019, Available :http://www.jetir.org/papers/JETIRFT06016.pdf

"Data Science or Predictive Analytics Requirements", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 3, page no. pp74-79, March-2019, Available at : http://www.jetir.org/papers/JETIRFT06016.pdf