Information policy is a guideline put in place by firm’s management to guide in the sharing, dissemination, acquisition, classification, and standardization of a firm’s overall information. Developing a database environment requires policies and procedures for managing organizational data as well as a good data model and database technology.
A formal information policy governs the maintenance, distribution, and use of information in the organization. Data administration is a company’s set standards that guide policies and procedures on how data is to be maintained to ensure it is resourceful.
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In large corporations, a formal data administration function is responsible for information policy, as well as for data planning, data dictionary development, and monitoring data usage in the firm.
Data quality assurance refers to the state of qualitative or
quantitative pieces of information to fit its intended uses in operations,
decision making and planning. Accurate, complete and consistent data create
accuracies in product pricing, customer accounts, and inventory data leading to
proper decision making.
1. What
are the advantages or disadvantages of data mining?
Data mining is the process that attempts to discover patterns in large volume datasets and transforming it into comprehensive formats for future use. Data mining has various advantages such as generating market data research that provides firms with large amounts of data for predicting market trends.
Data mining is also used by financial institutions to establish the credit scores of its clients. Nonetheless, data mining has various disadvantages such as leading to privacy and security breach issues.
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Some of the private information collected by firms may fall in
unauthorized hands and can be used in an unethical way such as cyber-bullying.
Personal information about employees including social security numbers, birth
details, payroll details, and copies of testimonials when not kept safely can
lead to identity theft, especially when it is accessed by hackers and conmen.
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