(a)
Define Data.
Explanation of Solution
Data are the raw facts and are referred to as the stored representation of events and objects that have importance and meaning in the user’s environment. Data can be structured or unstructured.
(b)
Define Information.
Explanation of Solution
Both the data and information are closely related to each other. Information is the data that is processed to increase the knowledge of a person who uses that data.
(c)
Define Metadata.
Explanation of Solution
Metadata is the data that describe the characteristics or properties of data used by the end user and the context of those data.
(d)
Define Enterprise resource Planning.
Explanation of Solution
Enterprise Resource Planning is a process of managing businesses. This process is used by many organizations to manage and integrate different parts of their businesses. It integrates all the important factors like product planning, manufacturing, development and sales.
(e)
Define Data Warehouse.
Explanation of Solution
Data Warehouse is a collection of large amount of data and information from different sources and management of that data to provide meaningful business insights.
(f)
Define Constraint.
Explanation of Solution
Constraints are used for specifying rules for the data in a table. It is used to limit the type of data to ensure reliability and accuracy of the data.
(g)
Define
Explanation of Solution
Database is a collection, organization, storage, update and access of data. Database makes data management easy.
(h)
Define Entity.
Explanation of Solution
Entity can be a place, person, object, concept or event in the user environment about which the organization wants to maintain the data.
(i)
Define Database Management System.
Explanation of Solution
Database management system is a software system that is used to create, store, update, retrieve, maintain and access user databases.
(j)
Define Data lake.
Explanation of Solution
Data lake is referred as a repository that stores a large amount of raw data in its native format. Data lake can store structured or unstructured data. Data lake stores data using a flat architecture.
(k)
Define System Development life cycle.
Explanation of Solution
System Development Life Cycle is a traditional method used to develop, maintain and replace
(l)
Define Prototyping.
Explanation of Solution
Prototyping is an iterative process involved in systems development in which there is a conversion of requirements to a working system which is revised continually through close work between users and analysts.
(m)
Define Enterprise Data Model.
Explanation of Solution
Enterprise Data Model creates an overall explanation and image of organizational data and not for a particular database. It may involve many databases and describes the scope of data maintained by the organization.
(n)
Define Conceptual Data Model.
Explanation of Solution
Conceptual data model is a detailed and technology independent specification of the overall structure of data of organization.
(o)
Define Logical Data Model.
Explanation of Solution
Logical data model is a data model that describes the data in a detailed format without considering how the data is physically implemented in the database.
(p)
Define Physical Data Model.
Explanation of Solution
Physical data model describes how data from logical data model is stored by a database management system. A physical data model consists of table’s structure that includes column name, primary key, constraints, data type and relationships between tables.
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Chapter 1 Solutions
Modern Database Management (12th Edition)
- 1. Complete the routing table for R2 as per the table shown below when implementing RIP routing Protocol? (14 marks) 195.2.4.0 130.10.0.0 195.2.4.1 m1 130.10.0.2 mo R2 R3 130.10.0.1 195.2.5.1 195.2.5.0 195.2.5.2 195.2.6.1 195.2.6.0 m2 130.11.0.0 130.11.0.2 205.5.5.0 205.5.5.1 R4 130.11.0.1 205.5.6.1 205.5.6.0arrow_forwardAnalyze the charts and introduce each charts by describing each. Identify the patterns in the given data. And determine how are the data points are related. Refer to the raw data (table):arrow_forward3A) Generate a hash table for the following values: 11, 9, 6, 28, 19, 46, 34, 14. Assume the table size is 9 and the primary hash function is h(k) = k % 9. i) Hash table using quadratic probing ii) Hash table with a secondary hash function of h2(k) = 7- (k%7) 3B) Demonstrate with a suitable example, any three possible ways to remove the keys and yet maintaining the properties of a B-Tree. 3C) Differentiate between Greedy and Dynamic Programming.arrow_forward
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