This book offers a journey through the new informational “space–time” that is revolutionizing the way we look at information through the study of Big and Smart Data for a zero-latency-connected world, in which the ability to act or react (in a pertinent and permanent way), regardless of the spatiotemporal context of our digitized and connected universe, becomes key.

Data (elementary particles of information) are constantly in motion (the Internet never sleeps), and once it is filtered, sorted, organized, analyzed, presented, etc., it feeds a continuous cycle of decision-making and actions. Crucial for this are the relationships between the data (their characteristics, format, temporality, etc.) and their value (ability to analyze and integrate it into an operational cycle of decision-making and actions), whether it is monitored by a “human” or an “automated” process (via software agents and other recommendation engines).

The world is in motion, and it will continue to move at an increasingly faster pace. Businesses must keep up with this movement and not fall behind (their competitiveness depends on it): the key to doing so is understanding and becoming an expert on the economic environment, which since the advent of the internet has become global.

Big Data was created relatively recently (less than five years ago) and is currently establishing itself in the same way Business Intelligence (technical and human methods for managing internal and external business data to improve competiveness, monitoring, etc.) established itself at the beginning of the new millennium. The huge appetite for Big Data (which is, in fact, an evolution of Business Intelligence and cannot be dissociated from it) is due to the fact that businesses, by implementing Business Intelligence solutions and organizations, have become very skilled at using and valuing their data, whether it is for strategic or operational ends. The advent of “cloud computing” (capacity enabling technological problems to be resolved by a third party) enables businesses (small- and medium-sized businesses now also have access to these tools, whereas they were previously the reserve of the large companies that could afford them) to facilitate and accelerate the implementation of Big Data. Following its rapid expansion in the early 2000s, Business Intelligence has been looking to reinvent itself; Big Data is establishing itself in this world as an important vector for growth. With the exponential “digitization” (via the Internet) of our world, the volume of available data is going through the roof (navigation data, behavioral data, customer preferences, etc.). For those who know how to use it, this data represents value and is a real advantage for getting one step ahead of the competition.

This move forward promises zero latency and connected businesses where each “event” (collected by data) can be tracked, analyzed and published to monitor and optimize businesses processes (for strategic or operational ends). This occurs when the two worlds managing the data meet: the transactional world (that aims to automate operational business processes) and the decision-making world (a medium for monitoring and optimizing business processes). For a long time, these two worlds were separated by the barriers of data “temporality” and “granularity”. The transactional world has a temporality of a millisecond, or even less for data processing that supports operational business processes, whereas the decision-making world has a temporality of several hours and in some cases even days due to the volumes, diverse and varied sources, and consolidation and aggregation necessities, etc., of data. It will be seen that using all (operational and decision-making) data is required to support decision-making processes.

Unifying the decision-making world and the transactional world will require businesses to rethink their information system so as to increase its interoperability (capacity to integrate with other systems) and to improve the temporality of the management of the data flows it exchanges. This is known as an event-driven architecture (EDA), and it enables normalized and no latency data to be exchanged between its components. The information system’s use value can therefore be improved.

Fernando IAFRATE

February 2015