Data mining In data mining, data is analyzed from various as well as diverse per
ID: 3862026 • Letter: D
Question
Data mining
In data mining, data is analyzed from various as well as diverse perspectives and then summarized into useful information for decision making. Different analytical tools are currently being used for this purpose. The data may be analyzed across different dimensions, which may be categorized in order to identify relationships among different variables.
Data Warehousing
Data warehousing is the process of centralizing or aggregating data from multiple sources into one common repository.
In computing, a Data Warehouse (DW) or Enterprise Data Warehouse (EDW), is a system used for reporting and data analysis. DWs are central repositories of integrated data from one or more disparate sources.
Action Items
- Give some examples where Data mining techniques are being used.
- Discuss different available tools and their benefits to the business industry.
- Identify current trends in Data mining and Data warehousing.
- Where do you see the future of Data mining in relationship with data warehousing in next ten years.
Explanation / Answer
Data mining techniques are used in many areas.Eventhough many challenges occur in this field,a number of commercial data mining systems are available today.
Data Mining techniques are mainly used in the following
a) Financial Data Analysis
b) Retail Industry
c) Telecommunication Industry
d) Biological Data Analysis
e) Other Scientific Applications
f) Intrusion Detection
The different tools available are
Rapid Miner (erstwhile YALE):
WEKA
R-Programming Tool
Python based Orange and NTLK
By using the different tools and techniques the following can be achieved.
Makes Web Data Extraction Easy
Data Processing Tasks Can Be Outsourced
Improve the Data Entry Process
Data mining tools and techniques are now more important and mainly used in all businesses, big or small.To make business decisions that will give them a competitive edge,we can apply the following techniques. Such actions based on data evidence and advanced analytics have better chances of increasing sales and facilitating growth. Adopting well-established techniques and tools and availing the help of data mining experts shall assist companies to utilize relevant and powerful data mining concepts to their fullest potential.
The concepts in data mining are still evolving and developing.The main trends that we can see in this field
Exploration of Application in different fields.
Finding data mining methods which are scalable and interactive
Database systems, data warehouse systems and web database systems should be integrated with data mining.
The meyhods to standardize data mining query language.
Visual data mining is a new concept
How to handle complex types of data and new methods for mining
Data mining in Biological field.
How to integrate software engineering and data mining.
Web mining methods
Distributed data mining.
Real time data mining.
Multi database data mining.
How to incoperate Privacy protection and information security in data mining.
The major trends in data warehousing includes the following
Data compression enables higher-volume, higher-value analytics.
In-database analytics simplify analysis
Data warehouses are more critical than ever to business operations.
Physical and logical consolidation help reduce costs.
Engineered systems are becoming a preferred approach for large scale information management.
Explosion of information can be achieved by comprehensive data warehouses that integrate operational data with customer, supplier, and market information.However, there is a growing gap between more powerful storage and retrieval systems and the users’ ability to effectively analyze and act on the information they contain. Both relational and OLAP technologies have tremendous capabilities for navigating massive data warehouses, but brute force navigation of data is not enough. A new technological leap is needed to structure and prioritize information for specific end-user problems. The data mining tools can make this leap. Quantifiable business benefits have been proven through the integration of data mining with current information systems, and new products are on the horizon that will bring this integration to an even wider audience of users.
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