Analytics and Data Science Fundamentals for Product Managers

Data Science and Analytics play a very important role in the field of Product Management, it helps product managers to make informed decisions, refined product performance, and create more effective strategies. Here’s an overview of Analytics and Data Science Fundamentals for Product Managers.

Analytics and Data Science Fundamentals

Here we will go over descriptive, predictive, and prescriptive analytics as well as the relationship between data science, artificial intelligence (AI), and machine learning (ML).

In this discussion, we will deep dive into the area of descriptive, predictive, and prescriptive analytics, exploring their distinctive roles and significance. Additionally, we will decode the intricate relationship between data science, artificial intelligence (AI), and machine learning (ML).

Let’s start exploring these concepts and how they relate to each other.

Three types of data analytics

1. Descriptive analytics
   Descriptive analytics is used to provide insights into historical events and current situations. This approach is vital in addressing queries regarding past occurrences or ongoing developments. Examples include using business intelligence tools, data visualization reports, and interactive dashboards.
2. Predictive analytics
   Predictive analytics helps answer questions about possible future events. Examples include financial forecasting and other predictive scenarios.
3. Prescriptive analytics
   Prescriptive analytics guides decisions on what actions should be taken. Examples include simulations, optimization, and scenario analysis.

Let’s delve into the understanding of these three data analytics types using the example of Emergency Services.

1. Descriptive analytics
   - Informs that lots of people are arriving to the ER
   - Offering real-time data to understand the array of challenges emerging within the ER
   - This data assists in understanding the effect on vital Key Performance Indicators (KPIs) such as wait times and occupancy rates
2. Predictive analytics
   - Predict and forecast an increase in the number of patients over the upcoming 1 to 2…