Towards Standardization of Data – Focusing on Data Quality as a Service

Abstract

In today’s world Data Quality is the fundamental to the health of any organizations. This organization can be a private player in the business world or even it can be any national body managed and controlled by the government. Poor data quality leads to myriad problems and it is a monumental effort to standardize them manually. Data quality issues trace back their source to the early days of computing. A wide range of area specific practices to measure and improve the quality of data exist in the works. These solutions mainly target data which exist in relational databases and data warehouses. The recent advent of big data analytics and resurgence in machine learning demands evaluating the suitability relational database-centric approaches to data quality. In this paper, we plan to target data quality issues related to the Address World in the context of big data and machine learning, and devise a systematic and planned data governance-framework to improve the data quality of the Address as a whole, finally describe the approach to its implementation.