Advanced Analytics Overview

Welcome to the section on Advanced Analytics! This page will provide you with an overview of the concepts, techniques, and tools used in advanced analytics. Whether you're a beginner or looking to expand your knowledge, this guide will help you understand the complexities of advanced analytics.

Key Concepts

Descriptive Analytics: This is the first step in the analytics process, where we summarize historical data to understand what has happened.
Predictive Analytics: This involves using historical data to make predictions about future events.
Prescriptive Analytics: This takes predictive analytics a step further by recommending actions based on the predictions.

Techniques

Machine Learning: A subset of AI that involves the use of algorithms to learn from data and make decisions.
Data Mining: The process of discovering patterns in large data sets.
Text Mining: The process of extracting information from unstructured text data.

Tools

Python: A popular programming language for data analysis and machine learning.
R: Another programming language widely used for statistical computing and graphics.
Tableau: A data visualization tool that helps you create interactive dashboards.

Learn More

If you're interested in diving deeper into advanced analytics, we recommend checking out our Data Science Basics course. It's a great starting point for anyone looking to understand the fundamentals of data science.