Analytics and Artificial Intelligence (AI)

Artificial Intelligence (AI) is rapidly growing technology and has proven its solid presence in innovation around the globe. The powerful feature of AI is, it can be applied to any task that involves data and it has widespread influence. As always, the benefits comes with risks that must be managed and mitigated. AI also brings potential benefits with considerable risks which can be mitigated with careful adoption of AI.

The systematic computational analysis of data is called analytics. Data analytics can help us taking certain business decisions.

5 Ways of Data Analytics and Role of AI.

Descriptive Analytics - What has happened?

Descriptive Analytics is the process of data mining and data modeling from raw data in such a manner that data can be easily interpreted by human being. Descriptive Analysis describes your data in more meaningful way and gives you insights into the past.

Descriptive Analytic System needs not to be Artificially Intelligent because it just summarizes the data. Usually, the types of underlying data being used for Descriptive Analysis is a count or aggregate of a filtered column of data to which basic math is applied.

One of the most common examples of Descriptive Analytics is, insights of the Financials of a business setup.

Diagnostic Analytics - Why did it happen?

One step further from descriptive analytics, Diagnostic Analytics identifies anomalies in the data and drills down into relevant data sources for specific patterns using data mining to establish correlations to identify anomalies. Diagnostic Analytics takes to the root cause of why some particular event has happened in the business operations.

Diagnostic Analysis is bettered with augmentation of Artificial Intelligent. Applying AI algorithms in data mining of historical data and other relevant data sources helps identifying anomalies in the data which explains occurrences some specific events.

Diagnostic Analytics of data can answer you why there was more sales in a particular year without changing in marketing strategy.

Predictive Analytics - What could happen?

Predictive Analysis is the process of predicting the future events based on analysis of the historical data. Patterns found using diagnostic analysis of historical data can be used to predict the probability of some events that can occur in the future of a business operations.

Predictive analysis becomes more precise using augmentation of advanced AI algorithms on patterns found using drilling down of historical data. As the foundation of Predictive Analytics is the probability, there is no AI algorithm which can predict the future occurrences of an event with 100% certainty.

One of the best application of Predictive Analytics can be in determining what items a customer may buy together in a certain condition.

Prescriptive Analytics - What should be done?

Prescriptive Analytics is the process of improvement in the certainties of future events which are predicted through predictive analysis of the data based on historical data.

Using even more advanced AI algorithms along with various business rules and data modeling procedures, it is possible to find out different possible ways to improve certainty of occurrence of a predicted event.

Using Prescriptive Analytics, patient experience can be improved at a point of care by providing certain facilities and care at the right time.

Cognitive Analytics - Cause something to happen.

Cognitive Analytics is the process of finding the insights from structured and mostly unstructured data using self learning system and representing it in human understandable format.

Getting insights from structured, unstructured and combination of both data needs extensive use of AI Algorithms. In Cognitive Analytics unsupervised tasks are performed and analytic system learns itself from the changes in the behavioral pattern in a particular data source. Finally it gives human readable insights for decision making and business intelligence.

Reliable and up-to-date health information can be given to consumers using Cognitive Analytics.

Summary

Use of Artificial Intelligent (AI) in Analytics significantly improves the automation of an Analytic System.