Define the terms data warehousing, data mining, and big data.

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a) Data Warehouse:

A Data Warehousing is a process for collecting and managing data from varied sources to provide meaningful business insights. A Data warehouse is typically used to connect and analyze business data from heterogeneous sources. The data warehouse is the core of the BI system which is built for data analysis and reporting.

It is a blend of technologies and components which aids the strategic use of data. It is the electronic storage of a large amount of information by a business that is designed for query and analysis instead of transaction processing. It is a process of transforming data into information and making it available to users in a timely manner to make a difference.

b) Data Mining:

Data mining is the process of sorting through large data sets to identify patterns and relationships that can help solve business problems through data analysis. Data mining techniques and tools enable enterprises to predict future trends and make more-informed business decisions.

Data mining is a key part of data analytics overall and one of the core disciplines in data science, which uses advanced analytics techniques to find useful information in data sets. At a more granular level, data mining is a step in the knowledge discovery in databases (KDD) process, a data science methodology for gathering, processing, and analyzing data. Data mining and KDD are sometimes referred to interchangeably, but they’re more commonly seen as distinct things.

c) Big Data:

Big Data is a collection of data that is huge in volume, yet growing exponentially with time. It is data with so large size and complexity that none of the traditional data management tools can store it or process it efficiently. Big data is also data but with a huge size.

Following are the types of Big Data:

  1. Structured
  2. Unstructured
  3. Semi-structured
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