TECHNIQUES FOR OPTIMIZING THE RELATIONSHIP BETWEEN DATA STORAGE SPACE AND DATA RETRIEVAL TIME FOR LARGE DATABASES

There are large amounts of data generated in the information society every day; this data comes from various sources, like measuring devices, public administration, mass media, telephony, GPS, the movie industry, television stations, etc. Gartner, the author of the "hype cycle" concept, defines the "BIG Data" (BIGD) concept as "high volume, velocity and/or variety information assets that demand cost-effective, innovative forms of information processing that enable enhanced insight, decision making, and process automation". It is the single most hyped term in the market today. BIGD has drawn the attention of the IT and marketing research communities, with concrete results about "BIGD solutions" and significant resources being allocated for "BIGD projects". The objective of the hype cycle for BIGD is to help the decision makers to work with this concept in order to develop future activities in the context of the fundamental change of the cost-benefit equation terms. Optimizing the relationship between storage space and retrieval time for data stored as BIGD is a major challenge for research in the field.