Big data is data sets that are beyond the power of storage and processing capacity. A huge amount of data is generated from applications like the Internet, social networks, Bio-informatics, sensors, Weather forecasting, etc. Processing this huge dataset using Traditional database systems is impractical. To process these data sets, two processing techniques are used, one is the Batch processing technique and the other is the non-batch processing technique. In Batch processing, huge data are collected over a particular period, processed, and produced output. Non-batch processing includes continual input of data and processing in small time. As per thekinds of literature and papers in the field of big data processing techniques, it was found difficult for the new scholars to analyze the big data generated by various application areas with various processing techniques. In this paper, the suggestions of the most efficient and suitable processing techniques technique are given to process different types of datasets generated by various application areas, along with the challenges in storing and processing and the advantages of analyzing them. Suggestions of the most efficient techniques will help new scholars to opt for better techniques to handle big data generated by various applications and to give optimum results.