Using Kettel for Data Quality & Integration

** You have to take screenshot for every step in the program (Kettel) and send it to me in a separate file please.

** the main instruction for this order **

It is investigation of data integration issues, you have been asked to perform an integration of sample excerpts from the membership details databases of both organisations. The membership databases excerpts only provide a small sample of the total datasets, and are also limited to only a small number of attributes for each customer record. So, you should perform:

1. An initial quality assessment of the datasets provided by both gyms.
2. Design and perform an integration of the datasets
3. Evaluate the integration process through an investigation of resultant dataset quality.

** I will upload 4 cv files to used it.

the integration project should identify:
1. Such overlapping customers, 2. As well as
a. eliminating replication of information within individual gym datasets, and b. providing a master dataset of contact details for the new merged gym.
More specifically, in order to complete this project you will need to:
 Investigate the properties of the three datasets with a Data Quality investigation. You may conduct this investigation with the DataCleaner Kettle plugin or any other kettle step that you find suitable (for example fuzzy match).
 On the basis of this project specification and your initial investigation, you should design and implement a Data Integration project to:
o Eliminate replicated records found in either Globo Gym or Average Joe’s datasets.
o Identify any customers who are potentially shared by both Average Joe’s and Globo Gym
o Create a new master customer list with standardised information on all customers. Standardised here refers to the use of consistent customer information representation on address, date of birth, and so forth.

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