Workshop Leader: Mazhar Javed Awan
Workshop Abstract
There is a need to process Big Data Analytics with efficient and compact manner. For this, Spark is the choice which works in-memory faster than MapReduce. Spark also includes prebuilt machine-learning algorithms and graph analysis algorithms that are especially written to execute in parallel and in memory. It also supports interactive SQL processing of queries and real-time streaming analytics. As a result, you can write analytics applications in programming languages such as Java, Python, R and Scala. Big data challenges include capturing data, data storage, data analysis, search, sharing, transfer, updating, information privacy and data source in the applications healthcare, business, engineering, IOT and Telecom.