• R.Sivakkolundu
• Dr.V. Kavitha

Every day large volume of data are generated across the world and put the information systems facing the emergence of big data phenomenon. The amount of data in world is exploding. Data is being collected and stored at unprecedented rates. The challenge is not only to store and manage the vast volume of data, but also to analyse and extract meaningful value from it. In the last decade Data Warehousing technology has been evolved for efficiently storing the data from different sources for business intelligence purpose. In the Age of the Big Data, it is important to remodel the existing warehouse system that will help us and our organization make the most of unstructured data with our existing Data Warehouse. The problem here is how to optimize data relevancy to extract value from the big data sources. From this Reasons, we propose an ETL and Map Reduce Hybrid Approach based on Data Filtering and processing to build an effective on-demand Dimensional Big Data, As Big Data continues to revolutionize how we use data, this paper addresses how to leverage big data by effectively integrating it to our data warehouse.

Dimensional Big Data, Data Filtering, ETL, Unstructured data, Hadoop Distributed File System

"A Hybrid Data Filtering Approach for Unstructured Data in Dimensional Big Data Warehouse", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 6, page no.392-397, June 2019, Available :http://www.jetir.org/papers/JETIR1907516.pdf

"A Hybrid Data Filtering Approach for Unstructured Data in Dimensional Big Data Warehouse", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 6, page no. pp392-397, June 2019, Available at : http://www.jetir.org/papers/JETIR1907516.pdf