Continuous Intelligence

Businesses are adapting to the change of digital transformation rapidly. The need for data exploration and big data analytics has always been growing. Until recently, a major challenge emerged. Data exploration needs to become quicker and constantly updated even for complex data that is different, large and unstructured. This is where the idea of Continuous Intelligence (CI) arises, designed to analyze all categories of data in real-time.

Definition of Continuous Intelligence

It is a design pattern in which actual analytics are combined into business processes, treating up-to-date and old data to propose actions in answer to business moments. In other words, it is a tool wherein the analysis of all categories of data is combined into business processes in order to determine actions that answer back to commercial events and moments in real-time. It is a solution compelled by Artificial Intelligence that agrees a company takes advantage of data in a constant and comprehensive means from all potential sources. Continuous intelligence integrates data and analysis with transactional commercial operations and other real-time communications, supporting technologies such as optimization, augmented analytics, machine learning, and flow processing permitting for minimized human involvement all over the process.

How can Continuous Intelligence help your business?

Continuous intelligence can support your industry in more than one means.

Streamline Data to get Continuous Insights

Continuous intelligence is broadly gotten by the actual accessibility of data, which in itself is a challenge for maximum companies. Businesses that gather massive volumes of data frequently lack a system that can pull the data to attain actionable insights. They are able to streamline the data to the exact position to implement artificial intelligence or get continuous intelligence out of it.

Improving Inventory Management

Various organizations prefer prescient models to arrange their inventory and assets. With the help of predictive analytics, these organizations can improve their stock maintenance and increase the quality of their assets as well.

Strengthen your Cybersecurity Strategy

Continuous intelligence also discovers its application in fraud detection and cybersecurity. A probable cybersecurity threat can proceed unobserved by an expert for many reasons. In such circumstances, an artificial intelligence and machine learning-driven Continuous intelligence system is able to throw out a suitable proactive comeback to the threat and, without disturbing the business processes, act on it founded on many data points. In other circumstances, it also is able to send out a suitable alert to the human forecaster responsible for the job, hence saving a lot of their effort and time.

A Real-time Example

The worldwide pandemic has caused radical ups and downs in buyer and worker behavior which has enforced digital transformation upon businesses. Machine learning classical training on regular behavior before the worldwide pandemic needed to be either reoriented or modified through human involvement.

One such case is that of the speedy shift in quest and buying behavior in April, where normal top ten searches of Amazon (phone chargers, cases, Lego) were entirely switched by COVID associated products (face masks, toilet paper, paper towels, hand sanitizer) in just a few days. Here is given the rapid change in the below graph.