How is data mining related to data science?
Data mining is the process of analyzing massive volumes of data to discover business intelligence that helps companies solve problems, mitigate risks, and seize new opportunities. This branch of data science derives its name from the similarities between searching for valuable information in a large database and mining a mountain for ore.
What are the six steps of data mining?
Data mining practitioners typically achieve timely, reliable results by following a structured, repeatable process that involves these six steps:
How is a decision tree used in data mining?
Decision tree: This data mining technique uses classification or regression methods to classify or predict potential outcomes based on a set of decisions. As the name suggests, it uses a tree-like visualization to represent the potential outcomes of these decisions.
How is data mining used in IBM Watson?
IBM Watson Discovery digs through your data in real-time to reveal hidden patterns, trends and relationships between different pieces of content. Use data mining techniques to gain insights into customer and user behavior, analyze trends in social media and e-commerce, find the root causes of problems and more.
Which is the best application for data mining?
Big Data is available even in the energy sector nowadays, which points to the need for appropriate data mining techniques. Decision tree models and support vector machine learning are among the most popular approaches in the industry, providing feasible solutions for decision-making and management.
How to solve real world data mining challenges?
Solve real-world data mining challenges. The Data Mining Specialization teaches data mining techniques for both structured data which conform to a clearly defined schema, and unstructured data which exist in the form of natural language text.