API Data Extraction / Database Creation

We are looking for someone to extract and organize a large amount of data from the Kiva API. Kiva is an online “microfinance” portal that houses data on several hundred thousand “lenders” who make small “loans” to tens of thousands of “borrowers” around the world. We are interested in extracting data on loan activity, and lender and borrower characteristics and organizing the data into a relational database. The Kiva Api is very user-friendly and Kiva provides clear and detailed documentation on an instructional blog: [login to view URL] We’d like to collect all available loan data associated with any US lender that has had some site activity from 2008 to the present. Specifically the data is organized by association with one of these 4 objects: (1) Lender Data : For ANY lender from the U.S. who has activity on the site from 2008 to the present: - ALL fields from lender listing (lender ID, name, country, city, geo, image id) - ALL fields from lender detail (number of loans, number of invites offered, number of invites accepted occupation, member start date) - other available data? (e.g., registration date, age, gender, race, income, number of loan defaults experienced, number of successful loans) - loan payment date and loan ID of every payment ever made (i.e., even loans prior to 2008) - team ids (2) Loan Data For all loans associated with lenders referenced in (1) - ALL fields from loan summary (name, country, geo, town, posted date, activity, id, use, funded amount, borrower count, loan amount, fundraising status, sector, image id) - For fundraising status, include funded_amount and basket_amount when applicable - ALL fields from loan detail (e.g, journal_totals, payments, scheduled_payments, local_payments, disbursal_date) - Borrower ID(s) associated with each Loan - MFI Field partner ID (3) Borrower For all Borrowers associated with (2) - ALL available fields including demographics (e.g., name, location, age, gender, race), loan history (e.g., number of loans requested, number of loans repayed), and post date (4) MFI Field Partner Data - ALL available fields for every MFI Field Partner ID in (2) Deliverables: (1) Test Data Set – (4 csv flat files) and Data Key Please create a test dataset that captures all loan data linked to any Lender ID with site activity during the first month of 2008. Specifically this would involve creating 4 relational flat files corresponding with the data objects enumerated above. We will provide 25% of the full payment upon successful completion of this task. (2) Full Data Set (csv flat files / possibly relational) and Data Key If (1) is successful, and we decide to proceed to (2), we will provide the remaining 75% of payment upon successful completion of the full data. (3) API Scripts used in the Extraction