Essay Example: Draft Implementation Plan for the Enterprise Data Management

The main aim of writing this essay is to enable the utilization of the recommendations suggested to upgrade Third Star Financial’s existing statistics managing architecture. When making changes, different phases are implemented, and several employees from the firm have to be involved (Mosley, 2010).

Is your time best spent reading someone else’s essay? Get a 100% original essay FROM A CERTIFIED WRITER!

Order now

Implementation Outline

Phase 1

Make a backup of the existing data to prepare for the incorporation of the new technology, which will take a period of five to seven days.

Phase 2

This phase involves integrating and implementing Hadoop to replace current technology. The benefit of Hadoop technology is that it is an open-source system. Implementing this system will take not more than two days, depending on the network speed and an extra day for error detection and fixing (Yang, 2011). Integrating into this technology will depend on the amount of data available and will take five to seven days. The main challenge is that there might be a loss of data at the integration phase without proper handling. The next step is to buy or download and implement Teradata, which can take two to three days. The team will transfer existing data from the current system to the Teradata system and take five to seven days. The main challenge is that there might occur data loss, and buying Teradata can be expensive.

Phase 3

This phase involves utilizing elimination tools to eliminate unwanted files and data to make more volume that may affect the new system’s processes. It will take two to three days. Tests will be run to determine if the new technology functions well and ensure the new technology and equipment can collaborate to scrutinize information and handle information in the statistics store.

Phase 4

This phase will involve training the employees and staff to ensure they familiarize themselves with the new tools. The training will take an estimated period of five to seven days.

Management Attention

Implementing and using new technologies is a venture for the whole firm, not one person (Rockart, 2009). Data supervisors; they work on the received information, manage the Db (database)and give results grounded on the study, the IT section, information specialists and data engineers; accountable for making designs and information representations showing the procedures and amenities affecting information utilization and data quality, will be the most needed to integrate and sustain the new technology (Kraft, 2016). The data analyst rank is the most important in determining if the new technology works properly. The IT section will ensure that the new technology has no errors and faults and troubleshoot any emerging errors.

Management Requirements

The new technology having been fully implemented, Third Star Financial’s architecture will be stable and organized, resulting in a fully functional system and statistics store (Philbin, 2013). The firm’s data supervision and processes must be updated with new and current tools. Since the data supervision architecture is extra stable through modern equipment, the Third star may begin to create a handset phone application. Since the management phase is complete, phone applications should be developed and tried to determine if they suit the customer needs through the aid of software makers. It will improve the Third Star's processes and make it more accessible (Dietrich, 2012).

Technical Expertise

Integration must be carried out carefully, making no errors when the technical expertise is more familiar and has enough knowledge on the new tools and technology (Kalyuga, 1998). They must be experts and have familiarity with changing technology. They must be capable of operating with minimal errors. The technical team in the IT section must be able to find and correct any arising mistakes from the new system. The management team should know about technology and how it operates. They should be equipped with information to be able to utilize the latest tools with ease. They should also be able to respond to any questions based on the new technology system (Bryson & Daniels, 2008).

In conclusion, when implementing new technology in a company, the involved personnel must pay much attention to avoid errors such as data loss. The data analyst and data supervisor play a critical task in this transition process.

References

Bryson, J. R., & Daniels, P. W. (2008). Skills, expertise, and innovation in the developing knowledge economy: the case of business and professional services. International Journal of Services Technology and Management, 9(3-4), 249-267.

Dietrich, D., Adamus, T., Miner, A., & Steinhart, G. (2012). De-mystifying the data management requirements of research funders. Issues in Science and Technology Librarianship, 70(1) 9-12.

Dreibelbis, A. (2008). Enterprise master data management: an SOA approach to managing core information. Pearson Education, India.

Kalyuga, S., Chandler, P., & Sweller, J. (1998). Levels of expertise and instructional design. Human factors, 40(1), 1-17.

Kraft, Debra. (2016) Work-Life: Enterprise Data Architect Job Description. The Nest.

Mosley, M. (2010). The DAMA Guide to The Data Management Body of Knowledge (DAMA-DMBOK Guide), First Edition. Bradley Beach, NJ: Technics Publications, LLC.

Philbin, S. P. (2013). Emerging requirements for technology management: a sector-based scenario planning approach. Journal of technology management & innovation, 8(3), 34-44.

Rockart, J. F. (2009). Chief executives define their own data needs. Harvard Business Review, 57(2), 81-93.

Van Oosterom, P., Martinez-Rubi, O., Ivanova, M., Horhammer, M., Geringer, D., Nevada, S., ... & Gonçalves, R. (2015). Massive point cloud data management: Design, implementation, and execution of a point cloud benchmark. Computers & Graphics, 49, 92-125.

Yang, E. (2011). Set Up Apache Hadoop in Minutes with RPMs. Hortonworks.