OSU Students Uncover, Explain, & Predict with Data Miner’s Impressive Array of Data Mining Algorithms
Company Size
1,000+
Region
- America
Country
- United States
Product
- STATISTICA Data Miner
Tech Stack
- Data Mining Algorithms
- Graphical User Interface
- Parallel Processing
Implementation Scale
- Enterprise-wide Deployment
Impact Metrics
- Customer Satisfaction
- Digital Expertise
- Productivity Improvements
Technology Category
- Analytics & Modeling - Data Mining
- Analytics & Modeling - Predictive Analytics
- Application Infrastructure & Middleware - Data Visualization
Applicable Industries
- Education
- Software
Applicable Functions
- Business Operation
- Product Research & Development
Services
- Software Design & Engineering Services
- System Integration
- Training
About The Customer
Oklahoma State University (OSU) is a comprehensive, land-grant university and research institution known for its focus on people and opportunity. The university serves a large population of traditional students as well as many non-traditional students who are working full-time in industry. These non-traditional students bring a wide variety of real-world classification and prediction problems to the university, making it essential for OSU to have robust data mining tools at its disposal. The university's Department of Management Science and Information Systems, led by Dr. Dursun Delen, plays a crucial role in teaching data mining to graduate IT students and conducting academic research. OSU's commitment to providing high-quality education and research opportunities makes it a leader in the field of data mining and analytics.
The Challenge
Oklahoma State University (OSU) faced the challenge of equipping both traditional and non-traditional students with the tools necessary to solve a variety of classification and prediction problems. These problems ranged from predicting diabetic illnesses based on demographic data to forecasting financial indicators like the S&P 500 and foreign exchange rates. The university needed a comprehensive data mining tool that could handle these diverse requirements while being user-friendly and cost-effective. After evaluating several leading data mining tools, OSU chose STATISTICA Data Miner for its impressive array of algorithms, graphical interface, and web-based accessibility. The tool's ability to be launched as a web application was particularly appealing, as it allowed students to access it from any web browser without needing to install client-side components.
The Solution
OSU implemented STATISTICA Data Miner to address its diverse data mining needs. The tool was chosen for its comprehensive array of data mining algorithms, user-friendly graphical interface, and superior graphical capabilities. STATISTICA Data Miner allows users to create complete projects using graphical icons and connection arcs, which can be run all at once. The tool's web-based accessibility means that students can use it from any web browser without needing to install client-side components. This feature was particularly beneficial for non-traditional students who may not have access to university resources on a daily basis. The tool also supports parallel processing on multi-processor environments, dramatically increasing the execution speed of data mining projects. This was crucial for students who needed to meet tight deadlines. Additionally, STATISTICA Data Miner provides a rich set of data preprocessing and visualization tools, making it easier for students to analyze and interpret their data. The tool's deployment feature allows users to turn developed data mining models into production systems, further enhancing its utility for both academic and real-world applications.
Operational Impact
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