Executive Presentation
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Datawarehouseprosandconsslides-1.pptxJamie Vaughan 10 May 2018
Data Warehouse
Data warehouse
Pros and cons
Cost and return on investment
Consolidation of data saves on software and hardware as well as time in retrieving it.
Information about clients and market being made available makes the cost of investment acceptable
Organization is set to benefit through the fast and sound decision making enabled by data consolidation
Areas that will benefit are; procurement, compensation and valuation department
The major limitation is the redeployment of IT personnel as training cost will be incurred.
The cost of having a data warehouse is worth the investment as a data warehouse saves the organization on so many things. One of the things is through the consolidation of data which means that there is a sizable saved cost on software and hardware (Seiner). A lot of time is also saved and better and more reliable information is provided. Data warehouse also enables better decision making (Seiner)as data facts are readily available. The kind of information that could make the cost of investment more acceptable if it is in a data warehouse is the client data and current market trends; this means that the evaluation is readily available and compensation is done according to the current market situation preventing losses. The organization will benefit from having a data warehouse as the business process will be improved through fast, easy and accurate decision making and problem solving. The specific areas that will feel the benefit of the data warehouse is the procurement department and the compensation and valuation departments. One of the negative impact of investing in a data warehouse is the redeployment of IT personnel; this will require training which may be costly.
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Required resources
The resources required to have a data warehouse running are; 1. storage (cloud or non-premise), 2. software to collect data 3. human resource for maintenance
Acquiring these resources will mean the organization incurs extra cost.
However, they are essential in the collection and storage of information as well as maintenance and update of the systems.
There are three essential resources that the organization should have to make sure that the data warehouse is functional; storage, software and human resources (Cooladata, 2017). The organization will have to incur cost to provide storage either cloud storage or non-premise. It will also have to acquire software that will pull data from all their sources and have it stored. It will also have to hire staff for the maintenance (Cooladata, 2017). The storage facility is essential and should be of good quality and easy to access to ensure that data is not lost and that it is readily available for use. The software to collect data is very important in making sure that all vital information is collected and that it is stored without being altered. This will ensure that the decisions that are made are right as well. The human resource responsible for maintenance will ensure that the data warehouse is functional at all time and there are no errors. The personnel will also oversee the upgrading process.
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Information value
The data life cycle is what makes the data in the warehouse valuable
Business opportunities such as offering insurance covers in areas which are not widely covered can be easily noted.
Database management systems making data available makes it easy to solve problems.
The availability of a data warehouse makes the data more valuable through the integration and combination of information (drugdesigntech, n.d.). This combination and integration of data is what creates a data life cycle. This life cycle is easy to manage and provides a lot of information including historical and current data (drugdesigntech, n.d.). Through the evaluation of historical and current data the management is able to make vital investment decisions like new markets to insure that are possibly covered by few firms and are profitable. The use of a database management system helps in decision making and problem solving as it provides relatively all required information with ease and the required accuracy.
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Limitations
Limitations include; Data ownership and data rigidity
If the data warehouse incorporates the whole organization there is the risk of cost out-growing the benefits
The problem of data ownership can be solved by having trusted data managers; the problem of data rigidity can be solved by constant and frequent updates
One of the major limitations of a data warehouse is data ownership as data in the warehouse can be leaked to third parties causing problems. The data warehouse doesn’t have the required security measures to make sure data doesn’t leak. Another limitation is data rigidity; this leads to waste of time when the data is being translated for use (Thakur, 2016). A data warehouse doesn’t have the data flexibility that may be required for emergency decision making. The cost of running a data warehouse may outgrow the benefits that it gives in the end (Thakur, 2016). This is especially if the data warehouse is used all over the organization hence it will massive staff for maintenance and appropriate technology to ensure functionality always and this may end up being very expansive. The problem of data ownership can only be solved by ensuring that the data managers are trusted people in the organization. The problem of data rigidity can be solved by ensuring that there is constant data update always.
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References
Cooladata. (2017). Cooladata. Retrieved from the true cost of building a data warehouse: www.cooladata.com/cost-of-building-a-data-warehouse/
drugdesigntech. (n.d.). drug design data management solution services. Retrieved from data warehousing; create value with efficient data management: www,drugdesigntech.com/data-warehousing-creating-value-effective-scientific-data-management/
Seiner, R. S. (n.d.). data warehousing ROI; justifying and assesing a data warehouse. the data administration newsletter. Retrieved from tdna.com/data-warehousing-roi-justifying-and-assessing-a-data-warehouse/4780
Thakur, S. (2016). what is dbms. Retrieved from 9 disadvantages and limitations of data warehouse: whatisdbms.com/9-disavantages-and-limitations-of-data-warehouse/
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