  We identify two major steps in data analysis, data exploration for
understanding and observing patterns/relationships in data; and construction,
design and assessment of various models to formalize these relationships. For
each step, there exists a large set of tools and software. For the first step,
many visualization tools exist, such as, GGobi, Parallax, and Crystal Vision,
and most recently tableau and plottly. For the second step, many Scientific
Computing Environments (SCEs) exist, such as, Matlab, Mathematica, R and
Python. However, there does not exist a tool which allows for seamless two-way
interaction between visualization tools and SCEs. We have designed and
implemented a data visualization platform (DVP) with an architecture and design
that attempts to bridge this gap. DVP connects seamlessly to SCEs to bring the
computational capabilities to the visualization methods in a single coherent
platform. DVP is designed with two interfaces, the desktop stand alone version
and the online interface. To illustrate the power of DVP design, a free demo
for the online interface of DVP is available \citep{DVP} and very low-level
design details are explained in this article. Since DVP was launched, circa
2012, the present manuscript was not published since today for
commercialization and patent considerations.
