Zero latency refers to a general business objective in which rapidly changing information is available across the entire business, leading to more informed and coordinated business decisions.  It can also refer to the perfection of latency optimization; that is, the theoretical end point of ultra-low latency engineering. 

Is there such a thing as true zero latency? 

Not really. Even in theoretically perfect network conditions, packets cannot exceed the speed of light. A network with tightly composed geography can more easily achieve near zero latency than one in which packets travel further through space. However, the term zero latency is more often used today to describe optimal business operations using near real-time data rather than the technical problem of minimizing message transport. The latter is more often referred to as ultra-low latency. 

What are the business implications of zero latency? 

Zero latency, or the Zero Latency Enterprise, is an organization that makes appropriate investments in low latency infrastructure in order to help the organization see insights and make informed decisions based on up-to-the-second data input. A zero latency enterprise stands in contrast to traditional data analytics that rely on data warehousing reports that are run on a periodic schedule. Thus the business using traditional methods is reacting to information that is, at best, hours old and usually much older. In zero latency, the organization makes decisions based on holistic business data that is constantly refreshed. It also implies that real-time data is accessible in all departments and business functions and not just within IT or top leadership. 

What are the business benefits of zero latency? 

Zero latency delivers agility and business intelligence. An organization with zero latency data infrastructure can make more informed decisions and can iterate its decisions faster. For example, a retail organization using zero latency will know what customers are buying up to the second, rather than relying on a report about what was bought last week. Moreover, by including social media data in the decision-making they can make inferences about customer sentiment and correlate that sentiment with sales trends. They can roll out test campaigns and get immediate feedback on the success of those tests.

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