‘Big’ Data is a term we use for large and complex datasets.  Datasets are growing into ‘big data’ partly because of the proliferation of cheap and numerous sensing devices such as smart phones, wireless cameras, aerial drones and wireless sensing networks.

The ability to synthesize Big Data into meaningful analytics is a game-changer for any organization.  Transforming massive amounts of data into actionable insights has been an illusive goal… until recently.

Gartner Group’s definition of Big Data is widely used and states that “Big Data represents the Information assets characterized by such a High Volume, Velocity and Variety to require specific Technology and Analytical Methods for its transformation into Value”. The 3Vs have been expanded to other complementary characteristics of big data:

  • Volume: big data doesn’t sample. It just observes and tracks what happens
  • Velocity: big data is often available in real-time
  • Variety: big data draws from text, images, audio, video; plus it completes missing pieces through data fusion
  • Machine Learning: big data often doesn’t ask why and simply detects patterns
  • Digital footprint: big data is often a cost-free byproduct of digital interaction

The growing maturity of the big data concept fosters a more sound difference between big data and Business Intelligence:

  • Business Intelligence uses descriptive statistics with data with high information density to measure things, detect trends etc.;
  • Big data uses inductive statistics and concepts from nonlinear system identification to infer laws (regressions, nonlinear relationships, and causal effects) from large sets of data with low information density to reveal relationships, dependencies and perform predictions of outcomes and behaviors.

There are now numerous tools (some free) designed to ingest and analyze massive quantities of structured and unstructured data.  These tools require an organization to design an information architecture to capture, curate, search, share, store and protect their big data assets.

CIMATRI experts have been working with Big Data Analytics for more than two decades.  Our architects were among the first to design and deliver high-quality analytics to the expanding mobile communications markets.  Utilizing the first massively parallel computing platforms, we delivered timely analytics on Key Performance Indicators (KPIs) by crunching hundreds of millions of rows of relational data on a daily basis.

CIMATRI can help you formulate and execute a plan to make use of this game-changing technology.  Your organization can take advantage of the investments made by Big Data pioneers such as Amazon, Microsoft, and the US Government.