Data Management In A Business Context: Challenges And Benefits (Essay).

After successfully completing this assessment task, you should be able to:

• Demonstrate understanding of the fundamental concepts of long reports in a business context

• Conduct independent research

• Explain the issues and benefits associated with implementing an information system

• Produce a professional report for a business audience

In the first section of the paper, a discreet definition and explanation of the data management are done. In this part, a complete definition of the terms is done. In the second part, a case study of a company in Sydney is used. From the case study the problem are identified and in the subsequent parts the challenges will be identified, the benefits and finally recommendations given to the problems. Finally, a conclusion is given covering the main parts from the above parts (Seyfi, 2012).

Never forget flowers is a business entity based in Sydney. The business is five years old and has eighty employees occupying the various positions- consultants, managers, programmers and business analysists. The company makes delivery of the floral bouquets to the offices, homes and in various occasion. The company doesn’t personally sell flowers to the customers but the main role is to make delivery of the flowers on behalf of its customers. The company works on an online platform to make a delivery to the customers.

Accordingly, the company has a lot of data that need some expertise so as to have the information system improved to facilitate efficiency. The data included in the company’s system include customer’s order specification and confirmation, predetermined reminders, calendars, customers’ change request slot and the rescheduled dates. The management seems to improve the type of data that can be contained in the company’s information system since the data in the old system is too rigid and shallow thus rendering very few functionalities to the users. Also in the old system, there data ion the system is not giving a room for the customers to have an easy access to the system as result the management has identified the need for evolving the old system into a more streamlined system that is object oriented. Accordingly, the management has going steps ahead to looks for an expert in the data management to offer advice on the intended plan. By looking for expert advice, the management seeks to understand how some of the old functionalities from the old model could be dropped and in turn, some new functionalities included for effectiveness (Kurbel ,2008).

There are various types of data management systems. They range from the small systems used on the personal computers to magnificent complex systems that are mostly found in the mainframes. The following are some of the applications of the database uses; automated teller machine (ATM), flight reservation systems and the computerized library systems etcetera. DBMS vary greatly in terms of the structure and this can be organized as relational, flat, network and hierarchical. In addition to this, the internal arrangement can determine how flexible and quick the data can be extracted from the machine (Robbins, 2008).

Data management can be defined as the collection of the programs that facilitates one to store, extract and modify information from a database. The database can be viewed as a reserve or a repository for data in the computers. Once the data is in the repository, the information can only be accessed by the use of a program. It is thus important to note that the user interface has commands that the user applies to retrieve or to gain access to the stored data in the database. Most importantly, the information stored in the database has some prompts that are different from the other since the information stored is different from one computer to the other depending on the intended use. For example, in this particular business, the data about the flowers, delivery terms and the customer's details are some of the information that is stored in the database.

Data management systems

When changing over a system from the one that the employees are used to there are certain challenges that the system faces these include; cold reception by the employees. This is because the employees are always used to the old system and there is the tendency to stick to the old model. To that effect, the employees will tend to resist any attempt to evolve. The company will need to train the employees for a smooth transition. In the course of introducing the new system, the employee’s productivity will be reduced and this will imply that the company will record reduced results at this particular period. In the course of introducing the new information system the quality of work may be interrupted and this would mean scaring away of the customers (Hazzard, 2011).

On the other hand, in traducing new system to the business implies that the customer's services will improve. Upon effecting the operation of the new system more functionalities are introduced implies more interaction and this improves the relationship between the customers and the business. On aggregate, the system improves the face of the company and improves the returns of the business (Robbins, 2008).

Database management has evolved from time to time. In the modern times, the size of the data used has resulted in the use of servers’ technology so as to give back yup to operations that are taking place in the various environments. In the new model, there is the use of the remote procedure calls and the database triggers that facilitate the performance of the application. Database server incorporate enables data replication with the support of both the synchronous and the asynchronous operations.

In an attempt to add more functionalities in the old system, there is the need to optimize the queries as such, use of SQL as the language is important. The main aim for this is to have an efficient data management plan. It is because the language doesn’t give some specification on the database implementation details. Use of relational database format in the new system will make the system to be faster and so there will be some efficiency added to the output (Kunii, 2008).

Using of database technology trends, the database will be more in a business style and this will facilitate easy and fast data access and management. Through using the new fashion of the database, the user will be in a position to vary the types of the information used for example use of video, image data, and audio (Heathcoat, 2009).

Conclusion

Data management system is a set of programs that are used to access data from the database. Irrefutably, there has been a lot of evolution in data management thus introducing some new factors in the sector. New changes have brought a lot of evolution in the data management and the set of the data that can be handled in the repository (Bamnote, 2013).

Like any other changes in every industry, introducing new system attracts and in a great way affects the performance of the company. There are often some challenges that are associated with the changes amongst these include the resistance from the workers. The need for new expertise costs the business in training the employee on the use and the general performance of the new system. Conversely, new systems in most cases bring a lot of positive outcomes. Some of the associated benefits include improved quality of services, improved customers satisfaction and improving the profitability of the business. Also, data explosion can easily be managed by the use of more improved database management systems (Antonescu, 2015).

There are various types of the database management and these are used depending on the current case. The type of information and the nature of the data to be used in the database are among the type of the factors that are to be put under consideration before settling at a given database format. In relation to this, a lot of factors has changed so as to have the data used in the database being managed in the most appropriate manner amongst the changes that have been realized is the data optimization and the use of the servers to have the data managed and actual optimization being realized (Babcock, 2008).

References

Antonescu, I. (2015). Premises for Creating the Database and Knowledge Base of An Expert System for Dynamic Management of Renewable Energy Resources Under Uncertainty Conditions. Anuarul Institutului de Cercetari Economice" Gheorghe Zane"-Iasi, 24(1), 87.

Babcock, C. (2008). XML Databases Offer Greater Search Capabilities. Interactive Week.

Bamnote, G. R., & Agrawal, S. S. (2013). Introduction to Query Processing and Optimization. International Journal, 3(7).

Doad, P. K., & Alaspurkar, S. J. (2010). Query Processing By Using Virtual Query Engine Tool.

Haithcoat, T. (2009). Relational Database Management Systems, Database Design, and GIS. Missouri Spatial Data Information Service presentations.

Halper, M. (2008). Welcome to 21st Century Data. FORBES, 157(7), 48-56.

Hazzard, E. (2011). OpenLayers 2.10 beginner's guide. Packt Publishing Ltd.

Infrastructure, D. S. Data and Databases. Databases, 3, 2.

Kaur, P. Optimization for a Distributed Query.

Kunii, H. S. (2008). Data Manipulation Language. In Graph Data Model (pp. 29-39). Springer Japan.

Kurbel, K. (2008). Design and Implementation of a Database with Innovative Business-lTo-Business Internet Applications. Journal of Computer Information Systems, 38(2), 8-13.

Ogutu, J. O. (2016). A Methodology to Test the Richness of Forensic Evidence of Database Storage Engine: Analysis of MySQL Update Operation in InnoDB And MyISAM Storage Engines (Doctoral dissertation, University of Nairobi).

Palvia, S. C. (2009). The effectiveness of asynchronous and synchronous modes for learning computer software for end users: An experimental investigation. Journal of Computer Information Systems, 41(2), 99-109.

Pons, A. P. (2007). A Practical System to Manage and Control Digital Media. Journal of Computer Information Systems, 47(4), 45-51.

Post, G. V., & Kagan, A. (2008). Comparison of database management systems. Journal of Computer Information Systems, 41(4), 43-46.

Robbins, R. J. (2008). Database Fundamentals. Johns Hopkins University, rrobbins@ gdb. org.

Seyfi, M. (2012). Gravitational Data Model for Databases. In Advanced Materials Research (Vol. 403, pp. 787-794). Trans Tech Publications.

Silberschatz, A., Stonebraker, M., & Ullman, J. (2010). Database research: achievements and opportunities into the 1st century. ACM Sigmod Record, 25(1), 52-63.