Airtable Database Optimization & Data Scraping
Budget: €30 – €250 EUR
Hi there,
I have a database in Airtables that contains 10 tables with about 10 fields each (average).
I am looking for someone to:
1. Create an interface containing a form that follows this hierarchy and characteristics
Project ─► Buildings ─► Apartments ─► Room Types ─► Sections ─►Worktype─► Interventions
The children are always multiselect i.e., Projects might have many buildings, buildings many apartments and so on.
2. Obtains intervention costs from table "Master renovations table" and rolls them up through each of the hierarchy levels.
3.Perform Scrapping on items found on two tables in four websites (Materials & Machines) and connect these to the "Master renovations table".
4. Perform scrapping on items found on idealista.es following a set of criteria and store them in a table called "Potential properties". Some of the input fields of the scrapping might change, set up to allow easy change should be considered.
Expectations:
1. Meeting to review and understand exact requirements, answer questions and start working.
2. Daily deliverables and updates on progress.
3. Automated daily/weekly scrapping of prices.
4. Fully functioning form/interface with needed functionality.
5. Completion in under 3 days.
I have a database in Airtables that contains 10 tables with about 10 fields each (average).
I am looking for someone to:
1. Create an interface containing a form that follows this hierarchy and characteristics
Project ─► Buildings ─► Apartments ─► Room Types ─► Sections ─►Worktype─► Interventions
The children are always multiselect i.e., Projects might have many buildings, buildings many apartments and so on.
2. Obtains intervention costs from table "Master renovations table" and rolls them up through each of the hierarchy levels.
3.Perform Scrapping on items found on two tables in four websites (Materials & Machines) and connect these to the "Master renovations table".
4. Perform scrapping on items found on idealista.es following a set of criteria and store them in a table called "Potential properties". Some of the input fields of the scrapping might change, set up to allow easy change should be considered.
Expectations:
1. Meeting to review and understand exact requirements, answer questions and start working.
2. Daily deliverables and updates on progress.
3. Automated daily/weekly scrapping of prices.
4. Fully functioning form/interface with needed functionality.
5. Completion in under 3 days.