A Survey of Various Tools and Techniques for Big Data Analytics

Data becomes big data when its volume, velocity, or variety exceeds the abilities of your IT systems to ingest, store, analyze, and process it. Many organizations have the equipment and expertise to handle large quantities of structured data—but with the increasing volume and faster flows of data, they lack the ability to “mine” it and derive actionable intelligence in a timely way. Not only is the volume of this data growing too fast for traditional analytics, but the speed with which it arrives and the variety of data types necessitates new types of data processing and analytic solutions. The volume, variety and velocity of Big Data causes performance problems when being created, managed and analyzed using the conventional data processing techniques.