Exploring Big Data Analysis: Fundamental Scientific Problems

Big Data From Scientific Simulations

Scientific simulations often generate massive amounts of data used for debugging, restarts, and scientific analysis and discovery. Challenges that practitioners face using these types of big data are unique. Of primary importance is speed of writing data during a simulation, but this need for fast I/O is at odds with other priorities, such as data access time for visualization and analysis, eff...

Exploring the Big Data Spectrum

Today, enterprises are flooded with data – terabytes and petabytes of it. Exabytes, zettabytes and yottabytes are definitely on the way. This tsunami of data, as some experts call it, which is growing exponentially, at a very high velocity from different sources in diverse formats, is being termed as Big Data. Big Data is the data pouring globally from transactional systems like SCM, CRM, ERP a...

Big Data: Promises and Problems

Big Data in High Performance Scientific Computing

Computation in science and engineering can be regarded as a focal point around which "revolves" the need to have knowledge of computer architecture, operating system, network technology, programming language, numerical algorithms, mathematical model, physical phenomena and theory of computation, respectively. If we discuss about the cluster or the computing center, and not about the supercomput...

Exploring Big Data using Visual Analytics

Never before in history data is generated and collected at such high volumes as it is today. For the exploration of large data sets to be e↵ective, it is important to include the human in the data exploration process and combine the flexibility, creativity, and general knowledge of the human with the enormous storage capacity and the computational power of today’s computers. Visual Analytics he...