1. WHAT IS DATA CENTRIC AI?
     Data-centric AI can be defined as artificial intelligence-based systems built around vast
amounts of data and using that data to learn and make decisions. These systems primarily use
machine learning techniques to analyze data trends, generate insights, understand patterns, and
make predictions.

2. HOW MANY DATA’S ARE THERE?
      Structured data, unstructured data, Nominal data, Ordinal data, Discrete data, Continuous
data.

3. WHY IS THE MOVE TO DATA-CENTRIC AI IMPORTANT?
    This significantly improves model performance and accuracy. Your data directly influences
your approach. Therefore, it takes less time to develop. This method leads to modern solutions as
it accommodates changing data. Trends and patterns can be explained by looking at the data,
increasing transparency. Data-centric AI can offer many benefits, including: B. Greater precision,
flexibility, efficiency, and transparency. These systems are even more reliable because they can
learn from large amounts of data and make predictions based on patterns and trends that humans
may not readily perceive. It will learn and improve over time as new data becomes available. A
shift to a data-centric approach is therefore an immediate imperative to better explore and harness
the power of AI.