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Questions and Answers
What is one of the objectives of data mining?
What is one of the objectives of data mining?
- To recognize the value in data sources (correct)
- To decrease data processing capabilities
- To consolidate data repositories into data warehouses
- To limit the availability of quality data
What has led to the availability of quality data on customers, vendors, transactions, and the Web?
What has led to the availability of quality data on customers, vendors, transactions, and the Web?
- Consolidation of data repositories into data warehouses
- Intense competition at the global scale (correct)
- Recognition of the value in data sources
- Decrease in data processing and storage capabilities
What is a key reason for the movement toward conversion of information resources into nonphysical form?
What is a key reason for the movement toward conversion of information resources into nonphysical form?
- Recognition of the value in data sources
- Consolidation and integration of data repositories into data warehouses
- Availability of quality data on customers and vendors
- Exponential increase in data processing and storage capabilities (correct)
What is a benefit of data mining?
What is a benefit of data mining?
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What is an example of a standardized data mining process?
What is an example of a standardized data mining process?
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Study Notes
Data Mining Objectives
- One of the primary objectives of data mining is to extract useful patterns, relationships, or insights from large datasets.
Data Availability
- The widespread adoption of technology, such as the Internet, mobile devices, and social media, has led to the availability of quality data on customers, vendors, transactions, and the Web.
Digital Transformation
- The need to reduce costs, improve efficiency, and enhance customer service has driven the movement toward converting information resources into nonphysical form.
Benefits of Data Mining
- A significant benefit of data mining is the ability to identify new business opportunities, detect potential problems, and optimize operations.
Standardized Data Mining Process
- The Cross-Industry Standard Process for Data Mining (CRISP-DM) is a standardized data mining process that outlines a methodology for data mining projects, covering business understanding, data understanding, data preparation, modeling, evaluation, and deployment.
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