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Data-Driven Decision making & Data Analytics

What is DDDM?

Data-driven decision-making (DDDM) is a process that involves using data and data analysis to inform and guide decision-making. The goal of DDDM is to use data to make more informed, accurate, and effective decisions. This approach involves collecting, analyzing, and interpreting relevant data and then using that information to make decisions that are based on evidence rather than intuition or guesswork. By relying on data and evidence, organizations can make more objective, consistent, and defensible decisions that are based on facts rather than opinions or assumptions. Additionally, DDDM can help organizations identify new opportunities, improve processes, make better use in better outcomes, and improve performance.


Data Analytics


Data analytics, e of resources, resulting refers to the use of data, statistical algorithms, and machine learning techniques to extract insights and knowledge from data. It is a broader term that encompasses data analysis but also includes more advanced techniques such as predictive modeling, data mining, and artificial intelligence. Data analytics enables organizations to analyze large and complex data sets, identify relationships and patterns, and make predictions about future trends.


Role of AI & ML:


With Artificial Intelligence and Machine Learning, the data is processed and analyzed by the Machine learning model. The machine learning model, in the sense that it is an algorithm, is an algorithm that will learn, analyze, and compare the inflowing data with the previously captured data and notify the user of any deviations in the data or process. In critical situations, AI will now make a decision or advise the user on which decision to scenario can be called "AI Driven Decision Making."  

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