Many organizations have large amounts of data which have been collected and stored in massive datasets which need be processed and analyzed to provide business intelligence, improve products and services for customers, or to meet other internal data processing requirements. This white paper provides an introduction to the HPCC Platform that solves large data processing problem.

Enterprise Control Language (ECL) is the query and control language developed to manage all aspects of the massive data joins, sorts and builds that truly differentiate HPCC (High Performance Computing Cluster) from other technologies in its ability to provide flexible data analysis on a massive scale. This white paper explores how ECL works and how it tackles data problems.

The principal performance driver of a big data application is the data model in which the big data resides. This paper discusses some of the principle data models that exist and are imposed; and then to argue that an industrial strength big data solution needs to be able to move between these models with a minimum of effort.

As a result of the continuing information explosion, many organizations are drowning in data and the resulting “data gap” or inability to process this information and use it effectively is increasing at an alarming rate. Data-intensive computing represents a new computing paradigm which can address the data gap using scalable parallel processing and allow government and commercial organizations and research environments to process massive amounts of data and implement applications previously thought to be impractical or infeasible.