Question: read and give your opinion in one line about this article?

Give some examples where data mining techniques are being used

The extraction of knowledge from the data revolution led by the tremendous development of technology, which facilitated the collection and extraction of data and then analyzed to make decisions .One of the most famous techniques of Data Mining

Statistics

not only answers these questions they help in summarizing the data and count it. It also helps in providing information about the data with ease. Through statistical reports people can take smart decisions. There are different forms of statistics but the most important and useful technique is the collection and counting of data. There are a lot of ways to collect data like :

Histogram

Mean

Median

Mode

Variance

Max

Min

Linear Regression

Clustering

Clustering is one among the oldest techniques used in Data Mining. Clustering analysisis the process of identifying data that are similar to each other. This will help to understand the differences and similarities between the data

Visualization

the most useful technique which is used to discover data patterns. This technique is used at the beginning of the Data Mining process. Many researches are going on these days to produce interesting projection of databases, which is called Projection Pursuit. There are a lot of data mining technique which will produce useful patterns for good data. But visualization is a technique which converts Poor data into good data letting different kinds of Data Mining methods to be used in discovering hidden patterns.

Decision Tree

Association Rules

Neural Networks

Classification

Discuss the different types of data warehousing architectures

Bottom Tier - The bottom tier of the architecture is the data warehouse database server. It is the relational database system. We use the back end tools and utilities to feed data into the bottom tier. These back end tools and utilities perform the Extract, Clean, Load, and refresh functions.

Middle Tier - In the middle tier, we have the OLAP Server that can be implemented in either of the following ways.

By Relational OLAP (ROLAP), which is an extended relational database management system. The ROLAP maps the operations on multidimensional data to standard relational operations.

By Multidimensional OLAP (MOLAP) model, which directly implements the multidimensional data and operations.

Top-Tier - This tier is the front-end client layer. This layer holds the query tools and reporting tools, analysis tools and data mining tools.

Explain the role of data warehousing in decision support

ETL Developer, BI Report Developer, BI Architects, Data Modeler ( Dimensional Modeler), BI Tester, BI Analyst, BI BA.

Discuss the different methods and algorithms of data mining.

The mining model that an algorithm creates from your data can take various forms, including:

A set of clusters that describe how the cases in a dataset are related.

A decision tree that predicts an outcome, and describes how different criteria affect that outcome.

A mathematical model that forecasts sales.

A set of rules that describe how products are grouped together in a transaction, and the probabilities that products are purchased together.