The Advantage of Data Warehousing Technology in Big Data and Data Mining

A data warehouse (DW or DWH), is also known as an enterprise data warehouse (EDW). Data warehousing is a system used for storing, reporting and data analysis technique that coverts raw data to a simplified required formatted data. DWs are the techniques where it tries to extract more value from larger data sets and tries to maintain central repositories of integrated data from one or more than one different sources. They store current and past data and are used for creating trending reports for senior management reporting such as annual and quarterly comparisons. The data stored in the warehouse is uploaded from the operational systems. The data may pass through an operational data store for additional operations before it is used in the data warehousing for reporting. The types of system consist data mart, online analytical processing (OLAP), online transaction processing (OLTP) and predictive analysis processing (PAP). A Big Data Warehouse (BDW) is an architecture for data management and organization that utilizes both traditional data warehouse architectures and modern Big Data technologies, with the goal of providing rapid analysis across a broad range of information types. This paper addresses some of the research challenges in Big Data Warehousing systems, proposing a vision that looks into: i) the integration of new business processes and data sources; ii) the proper way to achieve this integration; iii) the management of these complex data systems and the enhancement of their performance.