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High Level ETL and Data Mining Requirements - Research Paper Example

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These methodologies consider requirements specification as one of the early activities of the project (Miller & Han, 2001).
There are a few constraints…
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High Level ETL and Data Mining Requirements
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High Level ETL and Data Mining Requirements Introduction A Data Mining and ETL methodologies seek to organize the pattern discovery process in the data warehouse of an organization. These methodologies consider requirements specification as one of the early activities of the project (Miller & Han, 2001).High Level ETL ETL is the process in database usage especially data warehousing that involves the following activities:Extracting data from external sources.Manipulating data to fit the operational needs.

Loading data to the target.RequirementsBuild and Buy There are a few constraints that may prevent one from purchasing a product. After buying the hardware and software tools, one may not have enough money left for an ETL purchase. When considering on buying versus build, there are a few key items that can guide one in making the decision. The prices of ETL tools have not dropped over the last few years. It is important to evaluate the project keenly. Many people go for the expensive products without considering whether using a low-end or hand coding tool would be easy, fast or cost-effective.

When buying an ETL product, especially a more complex ETL, it will still be essential to train the project personnel. Training is more expensive than buying ETL for a project and should be considered when comparing the buying and development costs.Business Needs Business requirements are the functional requirements needed. They describe the needed solution in business terms. Gathering of information includes requirement interviews, workshop and enterprise objectives.Future Load Plans The future comes with questions as to how much is to be charged for products when combined with other suppliers products.

During the initial load improvement steps, all foreign key constraints are removed before executing the ETL stored procedure. The ETL stored procedure is called with a procedure that is truncated. ETL can be used to convert the data into a layout suitable for use in the new software. The initial load occurs in the analysis phase of the project. The timing to replace the tactical design choices is dependent on time on hand and the business requirements.Implementation Successful implementation starts with asking questions as to whether it is worth building the software, while it can be bought and used diversely in different applications.

If there is evident justification, then it is now appropriate to by the software.Recommendations The company should buy the tool because it is fast and the tool can be reused in other projects. The amount of ETL development time will be significantly reduced. The tools will be of a wide range and can be reused for future projects.Data Mining It is the practice of analyzing information from different dimensions and simplifying it in meaningful information (Clifton, 2010). It allows its users to examine data from many different proportions gives a summary of the relationships listed.

RequirementsData source- Determining which information source is to be utilized and where it is to accomplish its indented objective.Requirements contingency plans - It is necessary to define the contingency plans in order to address emerging problems or setbacks.Restriction requirements - It is necessary to identify requirements limits; they should be consistent.Classification and Clustering Classification and clustering are often mentioned in same categories, although they employ different approaches.

Clustering is a process to group related records together. Related records are categorized together on the basis of having similar characteristics. This approach is often used as an exploratory technique. This is because it is not necessary for the analyst to specify how records should be categorized together ahead of time. ReferencesClifton, C. (2010). Data mining. Encyclopedia Britannica. Retrieved from http://www.britannica.com/EBchecked/topic/1056150/data-miningMiller, H. J. & Han, J. (Eds.). (2001).

 Geographic data mining and knowledge discovery. London: Taylor & Francis.

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