- Introduction
- Basic Security Principles
- Data Management: Determining and Maintaining Ownership
- Data Governance Policies
- Roles and Responsibilities
- Data Ownership
- Data Custodians
- Data Documentation and Organization
- Data Warehousing
- Data Mining
- Knowledge Management
- Data Standards
- Data Lifecycle Control
- Data Audits
- Data Storage and Archiving
- Data Security, Protection, Sharing, and Dissemination
- Privacy Impact Assessment
- Information Handling Requirements
- Record Retention and Destruction
- Data Remanence and Decommissioning
- Classifying Information and Supporting Asset Classification
This chapter is from the book
This chapter is from the book
This chapter is from the book
Data Mining
Data mining is the process of analyzing data to find and understand patterns and relationships about the data (see Figure 2.2). Many things must be in place for data mining to occur, including multiple data sources, access, and warehousing. Data becomes information, information becomes knowledge, and knowledge becomes intelligence through a process called data analytics, which is simply examination of data. Metadata is best described as being data about data. For example, the number 212 has no meaning by itself. But qualifications can be added to give it meaning; for example, if you learn that 212 is an area code, then you understand that the number represents an area code in Manhattan.
Organizations treasure data and the relationships that can be deduced between individual data elements. These relationships can help companies understand their competitors and the usage patterns of their customers and can help them target their marketing. For example, diapers may be located in the back of the store, near the beer case, because data mining shows that after 10 p.m., more men than women buy diapers, and they tend to buy beer at the same time.
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FIGURE 2-2 Data Mining