Problem statementSend feedbackUp to now, we have learned about descriptive analytics in detail. Now we are starting to learn what Predictive analytics is. Based on the introductory video provided on Predictive analytics, which of the following do you think are the differences between predictive analytics and descriptive analytics?

Descriptive analytics and predictive analytics are two types of data analytics that serve different purposes and require different techniques and methodologies.

1. Purpose: Descriptive analytics is used to analyze historical data to understand what has happened in the past, while predictive analytics uses that data to predict what might happen in the future.

2. Techniques: Descriptive analytics often uses simpler statistical methods and data aggregation techniques to summarize data, while predictive analytics uses more complex techniques such as machine learning algorithms, predictive modeling, and statistical analysis to forecast future events.

3. Insights: Descriptive analytics provides insights into the past, answering questions like "what happened?" or "how often did it happen?". Predictive analytics, on the other hand, provides insights into the future, answering questions like "what could happen?" or "how likely is it to happen?".

4. Decision-making: Descriptive analytics helps in making informed decisions about the present based on past trends, while predictive analytics helps in making proactive decisions about the future based on predicted trends.

5. Data: Descriptive analytics deals with historical data, while predictive analytics deals with both historical and real-time data.

6. Complexity: Predictive analytics is generally more complex than descriptive analytics due to the use of advanced algorithms and techniques.

In summary, while both descriptive and predictive analytics are valuable tools for businesses, they serve different purposes and require different approaches.