Big Data and Data Mining: Concepts, Ethics, and Business Applications

Why is Big Data a priority for businesses?

Big Data provides valuable insights that can lead to better business outcomes.

What is Data Mining?

Data Mining is the detection, characterization, and exploitation of actionable patterns in business data.

What are the key characteristics of Big Data?

Volume, Variety, Velocity, and Veracity.

What is the difference between Big Data and Traditional Data approaches?

Big Data approaches are iterative and exploratory, while Traditional approaches are structured and repeatable.

What are some examples of data mining problems?

Understanding the problem, the size of the problem, the type of data available, and how to present the answer.

What is a Spiral Methodology in Data Mining?

A process that involves iterative exploration and refinement of data mining questions and methods.

What are some legal and ethical issues in Data Mining?

Privacy concerns, ownership issues, and the implications of European data laws on US practices.

possible discriminatory ; race , gender , age

How can data contamination affect data mining?

can lead to inaccurate

What does the term 'exploitation' refer to in the context of Data Mining?

Utilizing identified patterns and insights to drive business decisions and strategies.

What are the implications of discriminatory factors in data mining?

Data mining must avoid using factors like race, gender, or age that could lead to biased decisions.

What does 'characterization' mean in data mining objectives?

volume, velocity, and variety

What is the purpose of a video case study in a data mining lecture?

To provide real-world examples of how data mining is applied in business contexts.

What term is used to describe the subjects, such as product, customer, geographic area, and vendor, used to organize the data in a data warehouse?

Business dimension

What data warehouse architecture is based on a central data warehouse that stores the data plus multiple dependent data marts that source their data from the central repository in order to maintain a single version of the truth for decision-support purposes?

Hub-and-spoke

Domain expertise and text, numeric, and visual data are all inputs to what phase of the spiral methodology for the data mining process?

Problem Definition

Quality assessment, cleansing and normalization are tasks commonly performed in what phase of the spiral methodology for the data mining process?

Data Evaluation

'exploitation'