Survey of Big Data Warehousing Techniques

There is a growing need in the industry toward the development of new and sophisticated tools for storing the exponentially growing volume, velocity and variety of data, which is collectively referred to as big data. There has been a paradigm shift from traditional data warehousing techniques to inclusion of NoSQL technology in order to fulfill the requirements of big data. While Hadoop has powerful features, which is not a replacement to Data Warehouse, rather it is a complement. Data Warehouse is already good at processing structured data so when used in conjunction with Hadoop, it becomes a winning combination. Hadoop can be considered as one of the back ends of Data Warehouse for handling unstructured data. Hence there is research on enhancing existing Data Warehouse with new features that have been successful at handling big data, and most popular one among them is MapReduce. We discuss the different tools and techniques used for improving Data Warehouse by adding these features and discuss the limitations associated with them.