In this post, you will learn about how to turn data into information and then to actionable insights with the help of few examples. It will be helpful for data analysts, data scientists, and business analysts to get a good understanding of what is actionable insight? You will understand aspects related to data-driven decision making.
Before getting into the details, let’s understand what is the problem at hand?
The school authority is trying to assess and improve the health of students. Here is the question it is dealing with:
How could we improve the overall health of the students in the school?
We will look into the approach of finding the solution to the above question using the data while understanding the concepts of actionable insights.
Let’s quickly understand the journey of data to become actionable insights.
In the above diagram, you may see how the data got transformed from being raw data to insights. Here is an explanation:
Let’s learn about how could we turn data into actionable insights or how could we turn data to insights to action.
Here is the diagram representing how data could be transformed to action based on the insights gathered.
Let’s try and understand using the above example related to weights of students in the school vis-a-vis actionable insights.
The insight gathered from comparing mean weights of different age groups and classes against a benchmark resulted in finding out the classes and age group where the mean weights are less than or very near to the benchmark. These students could be termed underweight. This helps us in finding out students across different gender and classes where action need to be taken for improvement.
The next step is to design hypothesis around actions that could result in improving the weights of children. The following could be some hypothesis:
Based on the above, action could be taken. All or some of the above actions could be taken. After the action is taken, the data is captured again, presented in a suitable format and insights studied to measure the effectiveness of the actions taken. This is how one could go from data to insights to action.
The combination of Retrieval-Augmented Generation (RAG) and powerful language models enables the development of sophisticated…
Have you ever wondered how to use OpenAI APIs to create custom chatbots? With advancements…
When building a Retrieval-Augmented Generation (RAG) application powered by Large Language Models (LLMs), which combine…
Last updated: 25th Jan, 2025 Have you ever wondered how to seamlessly integrate the vast…
Artificial Intelligence (AI) agents have started becoming an integral part of our lives. Imagine asking…
In the ever-evolving landscape of agentic AI workflows and applications, understanding and leveraging design patterns…