Data Science is a field about processes and systems to extract knowledge or insights from data in various forms, either structured or unstructured. Data science employs techniques and theories drawn from many fields within the broad areas of mathematics, statistics, operations research, information science, and computer science, including signal processing, probability models, machine learning, statistical learning, data mining, database, data engineering, pattern recognition and learning, visualization, predictive analytics, uncertainty modeling, data warehousing, data compression, computer programming, artificial intelligence, and high performance computing. Methods that scale to big data are of particular interest in data science, although the discipline is not generally considered to be restricted to such big data, and big data technologies are often focused on organizing and preprocessing the data instead of analysis. The development of machine learning has enhanced the growth and importance of data science.
Storage clusters provide a consistent file system image across servers in a cluster, allowing the servers to simultaneously read and write to a single shared file system. A storage cluster simplifies storage administration by limiting the installation and patching of applications to one file system. Also, with a cluster-wide file system, a storage cluster eliminates the need for redundant copies of application data and simplifies backup and disaster recovery. Red Hat Cluster Suite provides storage clustering through Red Hat GFS
High-availability clusters provide continuous availability of services by eliminating single points of failure and by failing over services from one cluster node to another in case a node becomes inoperative. Typically, services in a high-availability cluster read and write data (via read-write mounted file systems). Therefore, a high-availability cluster must maintain data integrity as one cluster node takes over control of a service from another cluster node. Node failures in a high-availability cluster are not visible from clients outside the cluster. (Highavailability clusters are sometimes referred to as failover clusters.) Red Hat Cluster Suite provides high-availability clustering through its High-availability Service Management component.
NLoad-balancing clusters dispatch network service requests to multiple cluster nodes to balance the request load among the cluster nodes. Load balancing provides cost-effective scalability because you can match the number of nodes according to load requirements. If a node in a load-balancing cluster becomes inoperative, the load-balancing software detects the failure and redirects requests to other cluster nodes. Node failures in a load-balancing cluster are not visible from clients outside the cluster. Red Hat Cluster Suite provides load-balancing through LVS (Linux Virtual Server).
High-performance clusters u use cluster nodes to perform concurrent calculations. A highperformance cluster allows applications to work in parallel, therefore enhancing the performance of the applications. (High performance clusters are also referred to as computational clusters or grid computing.)