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The Anatomy of Big Data: The four pillars and other stories


The real challenge for organizations is that nearly 80 percent of all information is in an unstructured format making it difficult to search, navigate and organize. Knowledge workers spend 25 percent of their time searching for information, structured and unstructured data that don’t work well together and solutions that work well on the Web but not in the enterprise. As inherently analytical scientist types, we like to build our house on a rock of solid primary and secondary research. 

In this article we explore the anatomy of Big Data from the perspectives of technology, emerging technologies, its challenges to organizations and individuals, the overall market, its business value and social media.

The four pillars of Big Data 

1. Big Tables: Structured, Relational, Tabular, Rows and Columns, Traditional

2. Big Text: Unstructured, Natural Language, Full Text, Grammatical, Semantic

3. Big Metadata: Data about Data, Taxonomies, Ontologies, Glossaries, Facets, Concepts, Entities

4. Big Graphs: Object Connections, Subject - Predicate - Object, Triple Store, Semantic Discovery, Degrees of Separation, Linguistic Analysis, Schema Free

The Big Data market 

According to Gartner, Big Data initiatives will drive more than $200 billion in IT spending over the next four years along with tremendous change in how Big Data is managed. McKinsey has predicted that businesses will get $3 trillion in business value from Big Data in the next several years. 

But what is really going on in the Big Data space is the IT departments’ lemming-like move to inexpensive open source solutions that are facilitating the modernization of data centers and data warehouses. And at the center of this universe is Hadoop. 


The good news is Big Data provides many more new types of data for analysis that are seminal in this millennium, which is all about the new data-driven culture of real-time decision making. 

As Brynjolfsson and McAfee MIT research shows, data-driven companies are in the top third in their respective industries and are five to six percent more profitable than those that are not data driven (HBR, October 2012). 

Multiple new and diverse Big Data sets add additional parameters to some business models that weren’t available before. For many CEOs Big Data is all about potentially disruptive business-critical Big Data. 

In summary, data is information and the characteristics of Big Data are all about high-volume velocity and a variety of information assets that facilitate new forms of decision-making that leverage these characteristics for competitive advantage. 

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