Influence of In-Memory Analytics on Big Data

Business data is growing at an average of 36% year so it is necessary to analyze such huge quantity of data. For this purpose in memory analytics paradigm is used. In-Memory Analytics is used for instant reporting and real- time analysis in the organization so that decision can be made at the fast speed. In this approach data resides in main memory of server. Revolution in advanced memory technology, drastic decline in the price of memory and evolution of multi core processors have changed the orientation of business intelligence query. In this paper, I studied the influence of in-memory analytics technology to solve the challenges (volume, velocity, variety) of Big data in an organization. Big data is characterized by the parameters, volume, velocity and variety. This approach is able to handle the issues of Big data in an organization because traditional architecture used for managing Big Data(Extract, Transform and Load data warehousing querying tool) is increasingly inefficient to handle it and unable to produce an accurate and continuous analysis. In-Memory Analytics technology is a quite powerful and innovative solution. This will become the predominant architecture for handling the Big Data in the very near future.