The challenge of Big Data is the modern crest of a digital wave that began with much earlier technologies. Even at the start of the information age, data specialists were acutely aware of the explosion of data production and the problems associated with handling it. In 1944, Wesleyan University librarian Fremont Rider warned that American University Libraries were doubling in size every sixteen years, a rate of expansion that could only have been answered by the capabilities of modern computing. While the historically rapid shift from analog to digital technologies is the background for state-of-the-art data solutions, it is also drives the avalanching creation of data that demands cost-effective efficiency for storage, retrieval, manipulation, analysis and visualization.
Big Data is commonly characterized by the dimensions of volume, variety, velocity, variability and complexity. In addition to these characteristics, each organization defines its Big Data scenario according to its data management needs. For some, a data set may present challenges in the hundreds of gigabytes, and for others it may exceed hundreds of terabytes before the need for change arises.
The need for data solutions spans a diverse range of industries, including GIS/Geospatial and other scientific concerns, network search, and commercial and financial enterprises. Current infrastructural requirements for handling data can amount to thousands of servers running massively parallel software. Cloud data management has more recently emerged as a leading solution for Big Data situations.
The term Big Data represents a challenge, but it also stands for solutions to that challenge. Experts at SGT are experienced and poised to supply innovative solutions for a wide range of Big Data needs.