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What is Data Mining?
Data mining is the way of finding patterns, anomalies and correlations within big data sets to predict results. With the help of large range of techniques, we can utilize this detail to increase revenues, minimize costs, reduce risks, and improve customer relationships and some other things.
Data mining is the inspection and analysis of big amount of data to find useful patterns and rules.
Data mining approach are used to make machine learning (ML) models that gives modern artificial intelligence (AI) applications such as recommendation systems and search engine algorithms. Data mining can be done by various programming language such as data mining wirth python, data mining with r etc.
What are the benefits of using Data Mining?
Data Mining has become one of essential techniques which applies in all field to get performance of business. Organization can use various tools to do analysis of data by proper techniques applied. Some of the benefits of Data mining are discuss below:
What are the process of Data Mining?
- Minimize cost:-Data mining permits for efficient use and resources allocation. The Industries make plan and automated decision with proper forecasts that will provides bets result in the high cost reduction. The techniques have been applied in identifying the baggage’s of passenger and large amount of baggage’s can be handles without mishandling and most of customer get satisfaction which cut down in the searching and routing of missed bags.
- Exact prediction and forecasting:-Making plan is one of important and critical process within any company. Data mining provides planning techniques and gives managers with proper forecasts based on previous trends and present situation. Industry use this technique to know the proper inventory to efficiency of market requirement.
- Customer Insights:-It give the information during recognition of customer groups. Any organization deploy Data mining model from data of customer to hide key features and differences within their customers. It can be used to make personalize of every touch point to make better overall customer experiences.
- Automated decision-making:-Data mining helps the organization to make analysis of data and do automatic critical decision without wasting of time for person judgment. All the features have been implemented through program and works accordingly. As for Examples if someone trying to enter wrong password many times then it automatically blocks the entering of passwords and provides waring to the owner of the authorized access.
Before the occurrence of actual data mining, there are various process involved in implementation of data mining which are discussed below:
Who use’s Data mining?
- Business Research:-Before doing analysis of data, it needs to understand the objectives, resources availability and present situation in alignment with their need.
- Data Quality check:-The collected must be checked before implementation for data mining process. Data are collected from different sources and it required proper matched in data integration process.
- Data cleaning:-It has seen that most of time taken in cleaning, selecting and formatting data for before mining to get appropriate result.
- Data transformation:-This makes the data for final stages which comprises with five stages.
- Data smoothing
- Data conclusion
- Data Generalization
- Data Normalization
- Data Attribute construction
- Data modelling:-Various models are implemented in datasets which depends on different condition for get the better data patterns.
Presently Data mining has sued by many organizations to analysis of large amount of data to get appropriate result. Some of the areas are mentioned below where Data mining process used efficiently.
What are tools sued for Data mining?
- Educational:-In this field data mining helps the Institution to do proper analysis of course and keep the records of students and access the results of each students and make proper decision to provides special attention to low performance students. This helps educator to make better performance of students in their course work.
- Insurance company:-Company uses this technique to stop the fraud, risk and compliance of customer. With the help of this technique manager can analyses the profit of company and find different ways to offers their customer due to competition in market.
- Banking:-Now a days Data mining technique has become sone of essential part for banking sector. Due to automated making decision Bank has keep records of various transaction happening every second. Data mining helps organization to analyses the market value and do according to condition offering best rate of interest and other things for customers.
- Communication:-Data mining has used in communication systems to keep record of customers. Noe a day’s telecommunication company uses data mining techniques to customer call details make various offers according to demands.
Classification of Data mining System
- SAS:-SAS Data mining is one of accurate and important tool used for analysis of large amount of Data. The full Form of SAS is Statistical Analysis System which is product of SAS organization has developed for data management and analysis. The function of SAS is collected data, alter it and handle data from various sources and statistical analysis is performed. It also gives Graphical User Interface for non-technical users.
- IBM SPSS:-It is software developed by IBM company which is used for data mining and build the predicted model of data. Most of industry used this tool for analysis of statistical data. It is the visual interface that permits users to work smoothly for data mining techniques without programming requirements.
- SSDT:-It stands for SQL Server Data tools. It provides computing model that enlarge all the stages of database environment in the VS IDE. The users can use this tool directly and work directly connected database.
Data mining can be categories according to below criteria: -
Some of Terms of Data mining are:
- Machine Learning or Artificial Intelligence
- Database Techniques
- Data Selection:-It is the process where proper to the analysis work are recover from database. Data consolidation and transformation has performed sometimes before the data selection process.
- Data Integration:-It is the Business and technical process which is sued to attached data from various sources to gives a unified, and single view of data. It is used for Data virtualization, streaming of data integration, Data replication and change data captures.
- Clusters:-It is defined as the number of same things that occurred together. It refers to make groups of objects which are same to each other but more change from objects in different clusters.
- Data Transformation:-It is the process of changing the value, structure and format of data. Data can be transformed at two stages of data pipeline for data analysis projects. Some of the process involved in the data transformations are data integration, data wrangling, data migration and data warehousing. Data transformation has various aspects such as it may be constructive, aesthetic, destructive or may be structural.
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