Strategic advice to leverage new technologies

Coherence is a highly desirable characteristic of every human enterprise. Everything should "hang together" and be "true as a whole," to quote common dictionary phrases. Yet one of the most frustrating and disturbing aspects of working life is that everything doesn't hang together and isn't true as a whole. Most things only "sort of" fit -- if they fit at all. Gaps and inconsistencies abound. Assumptions must constantly be made.

A paradox increasingly confronts a number of researchers and analysts: to derive value from data, you need a lot of it. We now have the tools to analyze these large amounts, but few institutions, at least in the private sector, are willing to make it available to others.

For those not familiar with the structure of subways, the third rail is the one that carries the power for the trains. Under no circumstances do you ever want to touch it.

Big Data describes the evolutionary results of digitization, storage growth, and processing capability. It encompasses the growth of data in volume, variety, and velocity resulting from the increasing amounts of digitized material and data generated on the Internet.

As more traditional enterprises start to move their Hadoop projects into production, they are confronting the big question: How do we ensure data security and compliance in Big Data environments like Hadoop?

Big Data is inevitable and low latency is the need of the hour. Effectiveness in processing data has never been so relevant. If not engineered well, data processing systems that operate on Big Data are sure to suffer from performance problems. In this Executive Update, we explore an intuitive heuristic that will enable the user to understand the technical tradeoffs and learn how to performance engineer as well as tune a data processing system to effectiveness.

One of the most popular articles ever written for the Harvard Business Review was authored by Frederick Herzberg in 1968. 1 In it, Herzberg proposed a re