Data Mining Tools & Techniques With Processes
Nasr Ullah
![Nasr Ullah]()
Nasr Ullah
Building Secure, Scalable, and Smart Tech | Project Manager | QA Automation | Security Consultant
Data Mining is the practice of examining the large pre-existed data from any medium(databases, files etc) in order to generate the new information. Also we look for hidden, valid and potentially strong discovering patterns in datasets. It is also called the knowledge extraction and discovery, data analysis or pattern analysis.
We required multiple skills those are involved like databases, statistics, mathematics, machine learning and artificial intelligence.
We can perform the data mining on multiple number of types of data including but not limited to:
- Relational Database
- Distributed Database
- Data Warehouse
- Digital Data Warehouse
- Information Repositories
- Text Database
- Graphical Database
- Multimedia Database
- Live Streaming Database
- Text Mining and Web Mining
- Transactional & Spatial Database
- Legacy and Heterogeneous Databases
- Social Media(Facebook, Twitter, Google, Instagram, Pinterest etc) Text Database
Implementation Process
Techniques
- Classification
- Clustering
- Regression
- Outer
- Sequential Patterns
- Prediction
- Association Rules
Applications of Data Mining
- Education
- Retail
- E-Commerce
- Fraud Detection
- Insurance
- Bioinformatics
- Banking/Finance
- Manufacturing
and many more..
Tools
- Rapidminer
- Orange
- Weka
- KNIME
- SSDT
- Apache Mahout
- Oracle Data Mining
- Rattle
- DataMelt
- IBM Cognos
- IBM SPSS Modelr
- SAS Data Mining
- TeraData
- Board
- Dundas BI
- R-Language