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Types of Data Models and Schemas - Apadmi

University: UKBC COLLEGE LONDON

  • Unit No: 33
  • Level: Undergraduate/College
  • Pages 8 / Words 0
  • Paper Type: Assignment
  • Course Code: H/601/1991
  • Downloads: 0
Answer :
Organization Selected : Apadmi Ltd

INTRODUCTION

Database models and schemas are the layout which are used to store, manage, modify and retrieve useful data by arranging them in a systematic arrangement. With the growing processing data organisations require effective tools to manage complex data so that useful information can be gather from it. Database designing techniques also needs testing tools so that its effectiveness can be calculated and can ensure error-free data handling and processing. An appropriate control mechanism for verification and validation of implemented database is also necessary(Elmasri and Navathe, 2016). The report will describe the different database models and design techniques and tool which can be implemented for designing a relational database. The report also describes the limitations and benefits of these database techniques. It will also focus on structured query language tools for enhancing the user interface of database and to analyse the processes such as validation, verification and control mechanisms in database implementation.

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TASK 1

1.1 Different types of data models and schemas

Database models describes the logical constrains and inter-relationships between various data elements. Being one of the top most organisation in app development Apadmi Ltd (Manchester) follows efficient strategy to manage its huge amount of data via database models. Apadmi Ltd can employ any of the following database models:

  • Entity relationship database model: This database model effectively manages the real world entities. It gives conceptual design of database. Apadmi Ltd can use this model to manage its customer related data which include real-world attributes.
  • Hierarchical model: Apadmi Ltd can use this tree like model to manage data related to its internal working structure. In this model each record has single parent root whose child records are managed separately. This model gives Apadmi Ltd a strong command on records but it is less flexible(Pääkkönen and Pakkala,2015) .
  • Network model: This model utilizes set theory so each set of records consist of parent and child records. This model can easily implement the complex data relationships of Apadmi Ltd. This model gives data integrity to database management of Apadmi Ltd
  • Relational model: With this data model Apadmi Ltd can manage its data in the form of tables or relations. It consists of rows and columns which allows organisation to manage huge data without redundancy. However, it is complex and difficult to debug. Their main component is data dictionary which includes all records of other database objects(Veeraraghavan, Ramamurthi and Chen,2018).

Database Schemas: It is the visual representation of database rules which governs the database. It involves all attributes like types of data to be managed, constraints parameters, and keys involved in it. Apadmi Ltd can employ following database schemes.

  • Conceptual schema: This database schema focus on entities, constraints and data relationships instead of focusing internal storage details.
  • Physical schema: This database schema executes the translation of logical data structure into database definition through SQL statements(Coronel and Morris,2016).

1.2 Benefits and limitations of different database technologies:

Apadmi Ltd have great number of choices for database technologies such as Oracle, MS access, MySQL, DB2 and NoSQL.

  • MS access can provide easy installation and import facility in low cost along with data integration and multi user accessing support system. But for Apadmi Ltd it will not be suitable as Apadmi Ltd tends to handle huge amount of data.
  • Oracle is the best suitable for handling large amount of data of Apadmi Ltd but its installation, maintenance as well as operational cost are extremely high.
  • On the other hand MySQL can provide Apadmi Ltd feature of flexibility and open source platform at lower cost but it suffers from stability issues and has relatively poor performance scaling.
  • DB2 technology has low installation and maintenance cost and can support analytical and transaction related queries of Apadmi Ltd.
  • NoSQL database technology models are developed with low cost commodities. It can easily handle the big data thus from future perspective it is suitable but they require more expertise support for installation and maintenance(Zhang, 2017).

1.3 Different approaches for database designing:

Apadmi Ltd can use bottom up or top down approach for database designing. Although it can also use centralized and decentralized approach.

Bottom up approach: This database design approach is designed on the basis of previously existing relationship between different attributes of database. This approach is not common approaches because of its complexity involved. This designing approach is based on synthesis mechanism(Cotner and Miller,2016). In actual, the bottom up approach is considered as an approach in which there are various smaller subsystems made of the actual system. But a fact that is to be ensured here is that it somewhere gives rise to a system with more complexity and issues. Incoming of the information and data plays a very important role in bottom up approach, so the same can be adopted by Apadmi Ltd. while considering all the factors.

It is because this can actually help in covering the basic requirements and operations of Apadmi Ltd. There are variosu advantages of bottom up approach that can be considered by Apadmi Ltd and some of the well known examples of it can be considered as the fact that the positive factors will be reflected in every single task. Therefore, this can be termed beneficial. As if the employees of Apadmi Ltd will follow the bottom up approach, then it can help them in some factor in every single task. Custom adapters are also developed by their own in bottom up approach. After developing it, the employees may not have to put in extra efforts because it makes the operations easier and simpler than compared to other approaches.

Top down approach: This design approach executes database designing by analytical method. In this approach certain rules are identified after implementing particular relations, on the basis of which other relations of the database are determined. It eliminates redundancy and gives complete analysis of impact of attribute change. However, it is more time consuming as compare to bottom up approach.

Apadmi Ltd can implement a combination of both approaches to give optimize designing solutions. At the initial stage Apadmi Ltd can use top down approach while for executing amendments it can use bottom up approach. Top down approach is considered as a quite tactical approach. Although it is said that the overall coverage of the top down approach is limited but still, it involves the operations and processes tactfully that it can help in achieving of the operations and processes effectively.

This approach of database designing covers limited data because of its tactical nature. Apadmi Ltd on implementing this approach will have low impact on entire organisation. But on implementation of top down approach it is possible for the organisation to maintain a focused and wise utilization of resources. It will become a showcase for identifying the effective managerial solution. On completion of development phases of application Apadmi Ltd gets a matured, deeper solution for its database solutions.

In top down appraoch the operational and maintenance resources of Apadmi Ltd does not give significant impact initially as compare to that provided by bottom-up approach. There are certain disadvantages associated with this database designing approach. This approach provides a limited number of user access facility in the initial phases of development. This feature can influence the overall working of Apadmi Ltd. For achieving higher accuracy and efficiency Apadmi Ltd may also require installation of customized adapters.

TASK 2

2.1 Designing a relational database system

Dominican College can use various database tools and techniques which can improve the user interface for its course management database. Some of the most effective techniques which can be used for Dominican College are as follows:

  • Database with suitable colour choices and appropriate white spaces can enhance performance and reliability.
  • To specify the functionality, reliability and legacy proper implementation of tables, diagrams, focus adjusting tools, text and font formatting effects are mandatory tools. Such approach also provides the relational functionality(Coronel and Morris,2016).
  • White space is an important aspect in improving the quality of user interface for Dominican College database for course management. This white space can be improved by increase in white section and by tightening of line heights.
  • For achieving more usability the clickable area which is used to reach the destination of desired link, should be increased. This increment can be accomplish by adding padding links or by link to block conversion.
  • Highlighting the important changes and navigation so that keyboard related shortcuts are also enabled on web application of Dominican College database are also effective tools to enhance the performance and consistency.
  • Form fill and menu driven interfaces will allow users to have a clear idea regarding all available courses, and faculties. Users will be able to experience personalize interaction with the database(Armbrust, Xin, R.S., and Zaharia, 2015).

TASK 3

3.1 Benefits of manipulation and query tools in relational database system

Query tools or the structured carry languages are tools for database implementation. These tools allow user to modify the data stored in database without influencing the database schema. Data manipulation tools can enable Dominican College to make modifications, insertion, deletion to their course management database. Query and manipulation tools will make it easy for the Dominican College to specify what data is required by them for enrolling students. This will also guide desired aspirants to interact with database easily. These tools provide different capabilities and flavours for enhancing the functionality of relational database of Dominican College. One of the major advantage of query tools is that it does not require coding and can easily accomplish retrieve operation of huge amount of data(Krishnamurthy, Thombre and Hoyer,2014). Hence, database of Dominican College provides high performance and reliability solutions.

3.2 Implementing a query language in relational database management system

Various queries can be generated on the basis of the tables generated. Both the tables, Client and registration are composing of all the necessary entities. A few examples of queries are demonstrated as under :

  1. select coursefee

from Registration

where UnitID == 90

and Unit ==Fundamentals

  1. select courseID

from Client

where Lecturer == Mr Richid

and Coursefee ==2341

3.3 Extraction of meaningful data through query tools:

Dominican College need query tools which can extract the meaningful data from the piles of data stored in the database. Firstly the data stored in the database should be complete, as insufficient and incomplete data cannot be extracted. For instance if user do not fill their complete information like contact details or course details then database cannot extract the useful data. For extracting data, different types of queries can be used such as prediction and content queries which construct inferences on the basis of database model and input data. Content queries provides data statistics and other information. Database mining algorithm are use which can extract and transform the data stored into useful information(Armbrust, Xin, R.S., and Zaharia, 2015). Query tools detects pattern of text so that data can be analysed and Dominican College can have extract of meaningful data from entire database at any instant. Dominican College can use query tools such as R programming tools which can make statistics and can analyse the data along with graphical analysis. Another query tool which can be use for data extraction is Rapid miner tool. It is an open source tool and does not require coding. It gives advanced analysis of data with functions such as visualization, preprocessing and predictive approach(Linoff, G.S., 2015) .

TASK 4

4.1 Review and testing of Implemented database system:

The course management database system of Dominican Collegeneed to undergo testing procedures so that it can be evaluated that the database provides required output. Dominican College's database can be considered as heterogeneous as it will include various data types so testing of data base will analyse the presence of data integrity related errors. Such pre error analysis helps Dominican College to maintain the effectiveness and working of their database. The data base should meet security standards to avoid unauthorised access. Different users can access the college database from different platforms such as phones, tablets and computers so database should support them without errors.

Database testing also evaluates the size of different attributes in ideal cases and whether database is performing its basic storage, retrieval, insertion and deletion operations accurately or not. With testing tools it is also evaluated that user interface attributes are consistently mapped(Hazen, Boone and et.al,2014). It also monitors that front and back end operations responds simultaneously. The triggering can be tested in black box and white box stages. In white box testing Dominican College can use drivers and stubs for modifying data to produce triggers. In next phase of testing black box approach is used in which data is directly loaded to invoke the triggering parameter to test that intended work is accomplished or not.

4.2 Documentation to support testing and implementation of database:

Dominican College strongly requires the implementation of the course management database. With the database college will be able to easily manage its internal operations as well as end users also find its more comfortable to interact with the college via an easy user interface platform. There is a regular data flow between data base and user interface. To ensure that the continuity of this flow data mapping is essential which can be analysed by means of database testing. The implemented database system of Dominican College should meet all parameters of atomicity, latency and consistency and independences between various transactions. Database testing tools also provides test results for user defined functions operational accuracy, triggering and database schema related operations(Hazen, Boone and et.al,2014).

4.3 User documentation for developed database system of Dominican College

The database system designed for Dominican College for its course management, ensures that its user interface is as per requirement and meets all the necessary features. The students can navigate around different courses and the information related to them with the help of tabs. This allows the quick access of information without introducing multiple windows simultaneously. For accessing personalized information student can also use mailing conversation or can fill a form which includes basic details of them. The forms also help the Dominican College management to analyse the feedback and response of the students.

The lecturer’s also find it easy to fill their preferences for teaching. This data provides a great assistance to the management of Dominican College as they can easily analyse and can make suitable decisions. The database also consist of pop up and help menu's which guides its users regarding procedures such as which type of data they have to fill and how they have to submit their required information. The pop up menu helps Dominican College to receive instant feedback from users, so that errors and issues can be easily resolved.

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Current Legislation and Organisational Practices

4.4 Verification and Validation of database:

  • Verfication of database assure that Dominican College database system provides all functionality to it users such as students, lecturer’s and other visitors. On the other hand validation process is executed to test that the developed database system is meeting the requirements of users as well as of Dominican College.
  • Verification process is accomplished at the initial stage of database development so that database is error free and meets all requirement. On completion of verification process validation process is accomplished at the final stage of data base development process(Armbrust, Xin, R.S., and Zaharia, 2015).
  • Verification process reviews and inspect that the database is being implemented in desired manner. And once the implementation is complete validation process uses various testing methodologies such as triggering, black and white box test method to analyse the functionality as well as behaviour of database.
  • In verification stage code is developed and thus error elimination is less costly whereas in case of validation as code is executed so if error occurs in validation stage it is cost consuming process.
  • Verification process requires specifications and requirement list, various testing parameters, and test code. But since validation is performed at the final stage it requires complete final database(Cotner and Miller,2016).

4.5 Use of control mechanisms in database:

Dominican College database designing approach uses strict control mechanisms to ensure that the database strictly follows the required parameters and desired functionality is achieved. Dominican College can implement total quality management approach. This approach enables Dominican College to use effective strategy planning and communication for extracting the quality output. Under the total quality management controlling mechanisms Dominican College first emphasis on user satisfaction. It includes the complete analysis about the requirements of users, enhancement in data integrity and easy user interface. For adding regular developing features database must include new technologies and tools for designing(Weckenmann, Akkasoglu, and Werner, 2015).

Dominican College follows controlling execution at every stage so that continuous development results without any functional error. If some issue arises in data integrity or database functionality then Dominican College can acknowledge and improve them on the basis of feedbacks from the end user. For securing the data Dominican College also follows access controlling mechanisms which prevents unauthorised access. These controlling mechanisms are essential as database consist of sensitive informations of users which are necessary to protect from any kind of cyber threats. For monitoring this Dominican College can keep a track record of logins and logouts along with strong passwords.

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CONCLUSION

From the report it can be concluded that on the basis of organisational structure and requirement different data models such as relational, network, hierarchical can be used which gives data integrity and eliminated data redundancy for effective data management and handling. It can also be concluded that different designing approaches provides different ways to manage the data. The report also concludes that query tools consider the factors such as cost, user interface structure, legacy and consistency issues. The control mechanisms is mandatory for achieving the goals of verification and validation. It can also be concluded from the report that database implementation and testing techniques must appropriately utilize the query tools so that the meaningful data is extracted from the huge amount of stored data.

REFERENCES

  • Armbrust, M., Xin, R.S., and Zaharia, M., 2015, May. Spark sql: Relational data processing in spark. InProceedings of the 2015 ACM SIGMOD International Conference on Management of Data(pp. 1383-1394). ACM.
  • Coronel, C. and Morris, S., 2016.Database systems: design, implementation, & management. Cengage Learning.
  • Cotner, C. and Miller, R.L., International Business Machines Corp, 2016.Row-level security in a relational database management system. U.S. Patent 9,514,328.
  • Elmasri, R. and Navathe, S., 2016.Fundamentals of database systems. London: Pearson.
  • Hazen, B.T., Boone, C.A., Ezell, J.D. and Jones-Farmer, L.A., 2014. Data quality for data science, predictive analytics, and big data in supply chain management: An introduction to the problem and suggestions for research and applications.International Journal of Production Economics,154, pp.72-80.
  • Krishnamurthy, S., Thombre, N., and Hoyer, M., Cisco Technology Inc, 2014.Addition and processing of continuous SQL queries in a streaming relational database management system. U.S. Patent 8,745,070.
  • Linoff, G.S., 2015.Data analysis using SQL and Excel. John Wiley & Sons.
  • Pääkkönen, P. and Pakkala, D., 2015. Reference architecture and classification of technologies, products and services for big data systems.Big Data Research,2(4), pp.166-186.
  • Veeraraghavan, V., Ramamurthi, P.V. and Chen, Z., Huawei Technologies Co Ltd, 2018.Method and apparatus of maintaining data for online analytical processing in a database system. U.S. Patent 9,922,105.
  • Weckenmann, A., Akkasoglu, G. and Werner, T., 2015. Quality management–history and trends.The TQM Journal,27(3), pp.281-293.
  • Zhang, P., 2017. Practical Guide for Oracle SQL, T-SQL and MySQL.
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