Essay Example on Data Warehousing: Revolutionizing Independence Medical Center

Introduction

One of the uncollected core data on Independence Medical Center is data warehousing. Data warehousing is an information system comprising of communicative and historical data from multiple or single data sources. Data warehouse architectures are in three categories; single-tier architecture which removes data redundancy and minimizes the amount of stored data. The second category is the two-tier architecture which separates data warehouse and the physically available resources. The last type is three-tier architecture allows one to get data out from the data warehouse and shows an abstracted view of the database.

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

Save 25%

Data warehousing makes it easier for the analysis and reporting process of the organization data warehousing also plays a significant role in providing the truth for forecasting and decision making process in an organization.

Benefits of implementing a data warehouse

Independence Medical Center can benefit from data warehousing in many ways. Data warehousing streamlines the flow of information by facilitating the flow of information using a network. Data warehousing gives organizations a sure forecast in markets, results and identifies potential KPI's. Limitless access to information from various resources helps to deliver enhanced business intelligence.

Data warehousing saves time by storing information, integrating data, preserving, standardizing and aiding in consolidating data. It also ensures data consistency and quality data all through the organization. Data warehousing also provides a high return on investment (ROI) which enables the company to experience higher saving costs and revenues.

In an organization like Independence Medical Center, data warehousing will allow a competitive advantage since it is accessible to the current standing, and it evaluates the risks and opportunities. Data warehousing also maintains a cohesive database of the historical and current data, therefore, giving insights to the better decision-making process.

Challenges Facing Data Warehousing

Extra Reporting Work

The IT teams are responsible for generating different kinds of data needed in the warehouse. This process may end up involving the gathering of data from employees and customers, which was not there before.

Cost-Benefit Ratio

There is a higher expense in maintaining data warehouse and updating it as the company develops and adapts to the market. It may also be very inconvenient for the IT team to use a lot of budgetary money and time to come up with a tool that may not be used often and therefore, compromising implementation expense.

Data Ownership Concerns

Data warehouses are prone to data insecurities trust issues with whoever is accessing the data. The data warehouse may also leak customer personal data privacy, which may be a menace, especially to public relations. The service provider should ensure there is an individual analysis, especially from people one trusts.

Data Flexibility

Ad hoc queries tend to affect data warehouse on many occasion, and therefore it is hard to process the query speed and processing speed. Queries are often affected by ad hoc and thus limiting data relations during the assembling of data.

How Data Architecture Influences Internal and External Data-Sharing and Reporting Tasks

Data in the data warehouse are usually massive but updated, and daily data generation is easier. Thanks to big data that has enabled things to become easier. With big data, the data warehouses can reveal the trends, analyze the company's activities properly and monitor the industrial, economic behaviours. Internal and external sharing of data is made possible, and reporting tasks is even easier.

References

Guideline, N. S. F. DATA MANGEMENT PLAN.

Khan, S. I., & Hoque, A. S. L. (2016, January). Privacy and security problems of national health data warehouse: a convenient solution for developing countries. In 2016 International Conference on Networking Systems and Security (NSysS) (pp. 1-6). IEEE.

Shetty, S. J., Shaffer, S., & Vasseur, J. P. (2016). U.S. Patent No. 9,426,035. Washington, DC: U.S. Patent and Trademark Office.

Visscher, S. L., Naessens, J. M., Yawn, B. P., Reinalda, M. S., Anderson, S. S., & Borah, B. J. (2017). Developing a standardized healthcare cost data warehouse. BMC health services research, 17(1), 396.