Query Writing Skills And Issues Related To Integrity Of Database

The Schema and Tables in the Database

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2.A. Functional Dependencies

Functional dependency 1:

EMP_ID à CONTRACT_NO, HOURSASSIGNEDPERWEEK

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Functional dependency 2:

CONTRACT_NOà EMP_ID, HOURSASSIGNEDPERWEEK

Functional dependency 3:

HOTELNO àHOTEL_CONTACT_NO, HOTELLOCATION

Functional dependency 4:

HOTEL_CONTACT_NOà HOTELNO, HOTEL_CONTACT_NO

2.B. Insertion, deletion, and modification anomalies

In the given table, insertion, deletion and modification anomalies are present due to the un-normalized form of the relation. Now if the relation is decomposed up to 3rd normal form then it will eliminate all anomalies. Therefore, the given relation in 1st normal form is:

Emp_ID

Contract_No

HoursAssigned PerWeek

Hotel_contact_No

HotelNo

HotelLocation

2nd normal form:

Relation 1:

EMP_ID à CONTRACT_NO, HOURSASSIGNEDPERWEEK

Relation 2:

HOTELNO àHOTEL_CONTACT_NO, HOTELLOCATION

3rd normal form:

Relation 1:

EMP_ID à CONTRACT_NO, HOURSASSIGNEDPERWEEK, HOTELNO

Relation 2:

HOTELNO àHOTEL_CONTACT_NO, HOTELLOCATION

In the above two decomposed relations in 3rd NF are suitable solution to overcome these issues.

3. NoSQL

NoSQL can be defined as a method to design database which can easily accommodate a large variety of data models which is inclusive of key values, documents, formats of graph (Moniruzzaman and Hossain, 2013). No SQL stands for Not only SQL which is considered to be an alternative method of approach to database which is traditional in nature. In this method data is placed in various tables and schema of data which is designed in a careful way before the database is built. NoSQL database is considered to be useful for working before the database is built. NoSQL database is considered to be very useful for working various sets of data which is distributed.

The term of NoSQL can be easily applied to some of the database which can be overcome relational database management system (Pokorny, 2013). It is mainly referred to database which is built for the purpose of clustering of large scale database in various kinds of cloud and web services. In this kind of application needs of performance and scalability over checks the various kinds of issue of rigid data consistency.

Various organization round the globe like Google and Amazon makes use of NoSQL database so that they can easily focus various kinds of operational goals and implement relational database where high value of data consistency is required. NoSQL is a kind of database which is used for various web and cloud application which mainly tends to focus on specific idea of management of data (McCreary and Kelly, 2014). It has the ability to process large volume of data and quickly distributing that across various kinds of clusters which are considered to be desirable trait in cloud and web designing. Various developers who intended to create cloud and web systems are more flexible to create flexible schema of data which ultimately focus on the fact it enables fast or rapid changes to application which are generally updated on a continuous basis.                                                                     Figure 1: RDBMS vs NoSQL

Workforce Agency

                                                                     (Source: Created by author)

Key value store is a simple model of data which generally pairs a unique value of key with the value which is associated with it (Moniruzzaman and Hossain, 2013). Documents database is also known as document store is nothing but semi-structured data which is presented in document format. Document database provide developers with option to create and upgrade various kinds of program without the need of any kind of reference schema. Wide column stores organizes data in the form of columns instead of rows. Wide-Column stores can be found in the both forms namely SQL and NoSQL database. The basic structure of NoSQL is generally classified into various kinds of guides. In the various ranges of time vendors have mixed and matched elements in various form of NoSQL.

Graph store can easily organize data as nodes which can easily record in the form of relational database which mainly shows or represent connection between the nodes (McCreary and Kelly, 2014). There is other NoSQL database which have gained importance based on cloud based NoSQL database like Amazon DynamoDB, Google Big table and MangoDB.

There are list of advantages using NoSQL:

  • It can easily handle large volume of semi-structured, unstructured data as well as structured data.
  • It provides quick iteration and pushing of frequent codes.
  • It can easily handle OOPs or Object Oriented Programming language which is considered to be easy and flexible to use.
  • It has an efficient architecture which is cheap. 

References  

McCreary, D. and Kelly, A., 2014. Making sense of NoSQL. Shelter Island: Manning, pp.19-20.

Moniruzzaman, A.B.M. and Hossain, S.A., 2013. Nosql database: New era of databases for big data analytics-classification, characteristics and comparison. arXiv preprint arXiv:1307.0191.

Pokorny, J., 2013. NoSQL databases: a step to database scalability in web environment. International Journal of Web Information Systems, 9(1), pp.69-82. 

Arasu, A., Babcock, B., Babu, S., Cieslewicz, J., Datar, M., Ito, K., Motwani, R., Srivastava, U. and Widom, J., 2016. Stream: The stanford data stream management system. In Data Stream Management (pp. 317-336). Springer Berlin Heidelberg.

Gouhar, A., 2017. Database Management System. International Journal of Engineering Science, 11766.

Howard, N., Corcoran, N., Peters, J., Moon, D., Murphy, D., Kerger, M., Crowe, H., Xiberras, P., Hovens, C. and Costello, A., 2016. Caisis: A Prostate Cancer Database Management System for Translational Research.

Reddy, T.B., Thomas, A.D., Stamatis, D., Bertsch, J., Isbandi, M., Jansson, J., Mallajosyula, J., Pagani, I., Lobos, E.A. and Kyrpides, N.C., 2014. The Genomes OnLine Database (GOLD) v. 5: a metadata management system based on a four level (meta) genome project classification. Nucleic acids research, 43(D1), pp.D1099-D1106.

Singer, M., 2016, June. The application of a database management system in an energy management system. In Proceedings of the Ninth Power Systems Computation Conference (p. 359). Elsevier.

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