In the 2001 report “3D Data Management”, Douglas Laney of Gartner defined the three commonly accepted dimensions of Big Data that are Volume, Velocity and Variety. Volume is simply the amount of data available. Companies generate more and more digital information through customer interactions, transactional information, and social media just to name a few. They acknowledge the value of this data and therefore the volume of information available for analysis increase accordingly. Velocity is the ability of an enterprise to have access and utilise data in a fast way and to distribute it at an equally high speed. This not only requires physical bandwidth it requires architectures that balance data latency with data requirements. Finally this paper focuses on Variety or the range of data types and sources.
The variety of sources points to numerous types of data in various formats with different definitions and structures. While these issues have been addressed manifold – e.g. Master Data Management, one issue has received less attention: Putting this data in context.
This white paper looks at the enterprise information space and different data types. We outline strategies to combine data sets, referred to as Context Intelligence to drive visibility and more informed decision-making. Additionally, customer vignettes discuss applications of use case and value generation. The paper concludes with a number of suggested action items to jump-start the analysis of the largely untouched 80% of data.