Published Paper Details:

Data mining techniques are commonly used, and data warehousing plays a significant role in this process. The major difficulties in data warehousing have always been scalability and efficiency. Data warehousing is currently facing difficult hurdles in various areas as a result of the increasing development of data, and old methods are experiencing bottlenecks. As part of our research, we describe a document-based data warehouse. A distributed, document-oriented database is used to build the data warehouse in our technique of ETL, and the MapReduce framework is used for this.To highlight the facts of the situation, a case study is presented. The entire procedure when compared to RDBMS-based data warehousing, ours is more efficient. This method demonstrates increased scalability, flexibility, and efficiency. At its most basic level, the ETL process includes the extraction, transformation, and loading of data. Extraction, conversion, and loading are the three steps implied by the word, this basic description leaves out one important aspect: data transportation. The areas where each of these stages intersect