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A Data Model in software engineering is an abstract model that organizes and documents the business data for interaction between team members and is used as a plan for creating applications, how data are accessed and stored. According to Hoberman (2009), "A data model is a wayfinding tool for both IT professionals and business, which needs a set of text and symbols to precisely illustrate a subset of real information to enhance communication within the organization and thereby lead to a more stable and flexible application environment." A data model explicitly calculates the structure of structured data or data. Typical applications of data models add database models, enabling exchange of data, and design of information systems. Generally data models are described in a data modeling language.
Use a Set operator to create a list of academics who have written or co-written less than 5 papers and also have greater than 3 interests. List their academic number in the output.
Which is the properties of entities? Attributes is the properties of entities.
Question: Data Mining is the process of extracting knowledge hidden from large volumes of raw data. (a) Using a suitable example, illustrate how Data Mining can be useful t
With the linear commit protocol, sites are connected in a chain, and the subtransaction at the left-hand end of the chain initiates the protocol. Propose a crash recovery protocol
There are a number of possible solutions to the open ended brief. One of the simple ones is shown here without the PKs and FKs. It is important to think of how a number of tasks
Drawbacks of Database systems ?
Explain the rules for creating a labelled precedence graph for testing view serializability. Ans: A schedule S is view serializable if it is view equivalent to a ser
Probelm: a) In the context of OODBMS, define the following terms with appropriate examples. (i) Object class. (ii) Abstract class. (iii) Aggregation. (iv)
Explain the disadvantages of a file processing system? Ans: Disadvantages of File Processing Systems include: 1) Data Redundancy 2) Data Inconsistency 3) Difficult to acce
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