Artificial Intelligence enables computer systems to use a combination of data, logic, and mathematical and statistical methods to solve problems and make decisions. It includes applications such as machine learning and cognitive learning, which is the most well-known application of AI. 

Cognitive Learning enables computer systems to mimic human behavior when engaging in human interaction-related applications. A good example of AI is voice assistants found on many mobile devices and smart home devices. 

ML enables computer systems engaging in data-related applications to learn from data in real time by employing statistical algorithms and techniques. A good example of ML is a search engine that uses data to identify the most relevant results when a user searches for something online. 

Machine Learning Algorithms are formal statistical methods and processes to drive intended outcomes and generate predictions or forecasts. They use a series of mathematical steps to solve a data-related problem. There are many different types of ML algorithms for specific scenarios and applications. 

The algorithm implemented directly impacts the quality of results that can be obtained from given data set. Therefore, applying the optimal algorithm is critical when utilizing machine learning.

Big data refers to large volumes of complex data that continue to grow over time. The data is composited at variable speeds and times from a wide range of sources in a variety of formats and the volume of data can range from terabytes to petabytes.

The main challenge is robustly processing big data within relatively short intervals of time (days, hours, real-time etc.). Due to complexity and ambiguity, big data is difficult to fully comprehend using traditional processes, which makes AI ML essential for businesses seeking to understand their data.   

Data mining is a process of extracting meaningful information from large volumes of raw data. Data mining can identify patterns, trends, and connections in given data set based on certain criteria. Businesses can use insights from data mining in a variety of ways such as understanding customer behavior, designing effective marketing campaigns, and much more.