Data Mining is the process of extracting usable data from a large set of any raw data. Data mining is a key part of knowledge discovery that helps to analyse an enormous set of data.
Data Mining can also be defined as the process of sorting through large data sets in order to discover and identify patterns and establish relationship through data analysis.
1. Data Mining helps to extract information from a data set to give a meaningful insight for better decision making.
2. Data Mining helps in association/correlation between products sales.
3. Data Mining helps in checking competitors and monitoring market directions.
4. Data Mining helps in checking resources and spending.
5. Data Mining helps in checking and identifying criminality.
6. Data Mining helps to identify the kind of products your customers prefer per time.
7. Data Mining offers accurate market analysis.
8. Data Mining helps in fraud detection.
9. Data Mining helps in customer retention.
10. Data Mining helps in science exploration and research.
11. Data Mining helps in gaining higher returns on investment.
12. Data Mining provides job opportunity.
1. Data Mining implies analysis of data patterns in large batches of data using one or more softwares.
2. Data Mining has application in multiple fields such as fields like science and research.
3. With Data Mining, businesses can get more information about their customers and develop more effective ways to improve business functions.
4. Data Mining is used in effective data collection and warehousing as well as computer processing for arrangement and evaluation of the data.
5. Data Mining uses sophisticated mathematical algorithm.
6. Data Mining is also known as knowledge discovery.
7. Data Mining is a process used by companies to turn raw data into useful information.
8. With Data Mining, businesses can learn more about their customers to develop more effective marketing strategies, increase sales and decrease costs leading to higher profitability.
9. Data mining depends on effective data collection, warehousing, and computer processing.
10. Data mining can be used in a variety of ways, such as database marketing, credit risk management, fraud detection, Spam email filtering even to discern the sentiment or opinion of users.
The Data Mining process are broken down into these five steps:
1. Organizations engage in collection of data and load it into their data warehouses.
2. Organizations stores and manage the data, either in-house-server or on the cloud.
3. Business analysts, management teams and information technology professionals access the data and determine how they want to organize it for use.
4. Applications software sorts the data based on the user's results.
5. Lastly, the end user represents the data in an easy to share format such as in graphs or tables.
In the Full Course, you will learn everything you need to know about Data Mining with Certification to showcase your knowledge/skill gained.
Data Mining - Introduction/Overview
Data Mining - Tasks
Data Mining - Issues
Data Mining - Evaluation
Data Mining - Terminologies
Data Mining - Knowledge Discovery
Data Mining - Systems
Data Mining - Query Language
Data Mining - Classification & Prediction
Data Mining - Decision Tree Induction
Data Mining - Bayesian Classification
Data Mining - Rules Based Classification
Data Mining - Classification Methods
Data Mining - Cluster Analysis
Data Mining - Mining Text Data
Data Mining - Mining WWW
Data Mining - Applications & Trends
Data Mining - Themes
Data Mining - Exams and Certification
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