Exam 1: The Database Environment and Development Process

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The most common source of database failures in organizations is:

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Cost and complexity are just two of the disadvantages of database processing.

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In multi-tier database architectures, little functionality needs to be programmed into the client application.

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Personal databases are designed to support a small group of individuals working together on a project.

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Enterprise modeling sets the range and general contents of organizational databases.

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The systems development life cycle is the traditional methodology used to develop, maintain, and replace information systems.

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Data management technologies are also increasing often used as information systems, as a foundation for analytics or the systematic analysis of data to understand a real-world problem better.

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One reason for improved application development productivity with the database approach is that file design and low-level implementation details do not need to be handled by the application programmer.

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Specifying how data from a logical schema are stored in secondary memory is part of the:

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The physical structure and storage organization of the database is decided upon during the implementation phase of the systems development life cycle.

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Multi-tier client/server database applications contain a business logic layer.

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E. F. Codd developed the relational data model during the 1970s.

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A data model is a graphical system used to capture the nature and relationships among data.

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Languages, menus, and other facilities by which users interact with the database are collectively called a(n):

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A departmental multi-tiered client/server database is stored on a central device called a:

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Development starts from scratch with the traditional file processing approach because new file formats, descriptions, and file access logic must be designed for each new program.

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The steps of the systems development life cycle can only be viewed as a linear process.

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Database development begins with the design of the database.

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A physical schema contains the specifications for how data from a conceptual schema are stored in a computer's secondary memory.

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A major difference between data warehouses and transactional systems as compared to big data is:

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