The data in engineering and science has been on a massive scale and stored in gigantic storage devices. The data is moved in and out in the form of data streams. Data storage levels are reaching Yottabytes in terms of storage. Science and engineering transforms such data into rich and resourceful data. Intensive methods have been researched for high dimensionality. Science also uses high speed images and video data types in applications where data streams are reaching huge volumes with dynamic data distribution. Storage and computing such data is a challenging activity and especially in terms of system interactions and communications. Mining data streams is extracting knowledge in non stopping data streams. Research in this area has gained attraction due to the importance of its applications and the increasing potential of enhancement in streaming information. This paper discusses these challenges of data mining with a focus on issues like domain specific data integration, mining unstructured data, mining data streams.

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Data Streams Unbound Data Data Structures.