5 Types of analytics: Prescriptive, Predictive, Diagnostic, Descriptive and Cognitive Analytics

At different stages of business analytics, a huge amount of data is processed and depending on the requirement of the type of analysis, there are 5 types of analytics – Descriptive, Diagnostic, Predictive, Prescriptive and cognitive analytics. Whether you rely on one or all of these types of analytics, you can get an answer that as an analyst, a business owner or a data drive company needs to know- from what’s happening in their business to what solutions or best course of action to choose to bypass or eliminate future business issues.

Let’s discuss in details types of Analytics:

Descriptive Analytics:

As an analyst or a business owner, when you are looking for an answer of a question – What is happening in my business? This is when Descriptive analytics comes into place. It’s the most common and widely used analytics that analyses the data coming in real-time generally using effective visualisation tools like dashboards and allows us to learn from past behaviours, and give us an idea about how they will impact future outcomes.

But as it gives us only insight about whether everything is going well or not in our business but it didn’t explain the root cause behind this. For this reason, highly data-driven businesses combine descriptive analytics with other types of data analytics to find the complete solution.

You can think of Google Analytics tools and other web and social analytics tool as an example to understand Descriptive analytics.

Diagnostic Analytics:

When you already know what’s happening in your business using Descriptive analytics and you want to know that the answer of next question i.e. Why it is happening in your business or in general you want to know the root cause behind that, this is where Diagnostic analytics plays its part and helps analysts or data scientists to drill down inside the data to find the answer.

Generally, in business, BI dashboards help you drill down using hierarchies or do a quick comparison to find the reasons or factors that are effecting business.

Predictive Analytics:

Predictive Analytics is based on what you get from descriptive and diagnostic analytics and used to find answers to the question of what is likely to happen in the future based on previous trends and patterns? In general, it’s all about forecasting.

Predictive Analytics utilizes various statistical and machine learning algorithms to provide recommendations and provide answers to questions related to what might happen in the future, that cannot be answered by BI. But as it’s probabilistic in nature, it just gives an estimate of a possible future outcome. Also, the accuracy is not 100% because it all depends on data quality, how you make educated guesses on the missing values and how and optimization is done.

For example, in healthcare Predictive models typically utilise a variety of variable data like age, past treatment or illness history, BMI, cholesterol to make the prediction whether the person is susceptible to a heart attack or not.

Prescriptive Analytics:

When you get the findings from Descriptive, Diagnostic and Predictive analytics like what’s happened, the root cause behind that and what-might-happen in future, Prescriptive model utilizes those answers to help you determine the best course of action to choose to bypass or eliminate future issues.

You can use Prescriptive analytics to advise users on possible outcomes and what should they do to maximise their key business metrics.

The best example in front of you is Google Maps which helps you to choose the best route considering distance, traffic and speed.

Cognitive Analytics:

Cognitive analytics combines a number of intelligent technologies like artificial intelligence, machine-learning algorithms, deep learning etc.to apply human brainlike intelligence to perform certain tasks.

Basically, this type of analytics is inspired by how the human brain processes information, draws conclusions and codifies instincts and experience into learning such as understanding not only the words in a text but the full context of what is being written or spoken. All these intelligent technologies make a cognitive application smarter and more effective over time by learning from its interactions with data and with humans.

Conclusion :

As the basic goal of analytics is to discover and understand data to take an action, these 5 types of analytics, data-driven business are free to choose which analytics is best suited to satisfy their business needs.