Create a amall app with its own DB to import contacts files (in .csv) from 2 sources, compare them using Ai techniques to standardize fields

We need a small app created over AWS platform to import data 2 sources: - Italian Company Register (import data in xls) - Linkedin (import data in csv) elaborate them to standardize several fields and return a .csv properly formatted to be passed to another application ST1 create a database on AWS 1. Basic Tables (standard values, these table must be editable) - Categories - Industries - Italian Provinces (territories) - Role (by categories) - Status 5. Master Table Italian Registry (xls) -Companies&Locations 6. Master Table Linkedin Extractor (xls) 4. Companies Table (Linkedin_Id, Companyregisted_Id, Category, Industry, Adress, Status, ... all other) 2. Location Tables (each company may have more locations in Italy) 2. Employee Table (Linkedin_Id, Name, Surname, Mail, Role, ....all other) ST2 imports data from Italian registry in xls master table to its master Table avoiding duplicate records with the primary key unique set company status=to be qualified imports data from Linkedin extractor in csv to its master Table avoiding duplicate records with the primary key unique status=to be qualified ST3 3.a. import new records from data from Italian Register Master Table (IR_Pk, Company_name, Category, Adress, City, Province, Postcode, Country, etc) and set company status=to be qualified - Look up in Linkedin extractor Mastertable for a similar company names in all contact rows (with AI) if the match is 98% then match the 2 primary key and merge the rows on Output Company Table If the match is 95%-98% ask the operator for the correct match (show multiple solution) (IR_Pk, Company_name, Category, Location name, Adress, City, Province, Postcode, Country, Ld_Pk) - Look up in Linkedin extractor Mastertable for Industry_Linkedin using AI to standardize the company industry as in the table if the match is 98% then match the 2 If the match is 95%-98% ask the operator for the correct match (IR_Pk, Company_name, Category, Location name, Adress, City, Province, Postcode, Country, Ld_Pk, Industry) For each contact we should have 3-4 copanies actual and past 3.b. import location data from Italian Register Master Table (IR_Pk, ParentCompany, Location name, Adress, City, Province, Postcode, Country, Ld_Pk) 3.c. import individuals data from Linkedin Master Table and populate Company and Employee table (Ld_pk_individual, Ld_pk_company (parent), name, surname, email, phone) Use AI to standardize the "headline" to one of the 26 Job function this must be supervised form the operator (Ld_pk_individual, Ld_pk_company (parent), name, surname, email, phone, Job_function) Import all other relevant data from Linkedin Master table university etc - Import all other relevant fields from Lkdin If the operator gives the OK for all changes then set company status=qualified and individual status=qualified otherways status=in qualification INDIVIDUAL (Ld_pk_individual, Ld_pk_company (parent), name, surname, email, phone, Job_function, Qualified) COMPANY (IR_Pk, Company_name, Category, Location name, Adress, City, Province, Postcode, Country, Ld_Pk, Industry, Qualified) ST4 all company qualified must be extracted and passed in a proper csv format to be imported in another sys