![]() Therefore, Hadoop-based platform based on distributed scale-out storage system emerges to deal with big data. Hadoop-based platform is well suited to deal with not only structured data but also semi structured and unstructured data, and provides scalability and fault tolerance. Distributed scale-out storage system meets the needs of big data challenges. Traditional data warehousing is a large but relatively slow producer of information to analytics users and mostly ideal for analyzing structured data from various systems. Existing big data platforms cannot scale to big data volumes, cannot handle mixed workloads, cannot respond to queries quickly, load data too slowly and lack processing capacity for analytics. It requires massive performance, scalability and fault tolerance. Big data analytics is an area of rapidly growing diversity. ![]() Achieving the full transformative potential from the use of this massive data in increasingly digital world requires not only new data analysis algorithms but also a new generation of distributed computing platforms. Data continue a massive expansion in scale, diversity, and complexity.
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