DOCUMENT AI
Budget: €250 – €750 EUR
DOCUMENT AI GOOGLE . We are looking for people with proven capability document parsing.
Database design: necessary tables :
A) table for suppliers,
B) customers,
C) documents (invoices, orders)
D) products
Define the attributes of each table and the primary and foreign keys to establish the relationships between them.
Database creation: Use a relational database management system (RDBMS) such as MySQL, to create your database.
Data extraction: Use the information extraction techniques to extract the relevant data from the documents. Machine learning methods to extract the desired information and associate it with the corresponding database tables.
Data insertion into the database: Use SQL language or a data import tool provided by your RDBMS to insert the extracted data into the database. Use INSERT statements to insert records into the appropriate tables, following the defined relationships.
Quality control: Verify the correctness of the data inserted into the database. Run queries to extract the data and compare it with the original documents to ensure the accuracy of the extracted information.
Data querying and analysis: Use SQL language to query the database and retrieve data based on specific criteria.
Updating and maintenance: create scripts or automated procedures for inserting the newly extracted data into the existing database.
Database design: necessary tables :
A) table for suppliers,
B) customers,
C) documents (invoices, orders)
D) products
Define the attributes of each table and the primary and foreign keys to establish the relationships between them.
Database creation: Use a relational database management system (RDBMS) such as MySQL, to create your database.
Data extraction: Use the information extraction techniques to extract the relevant data from the documents. Machine learning methods to extract the desired information and associate it with the corresponding database tables.
Data insertion into the database: Use SQL language or a data import tool provided by your RDBMS to insert the extracted data into the database. Use INSERT statements to insert records into the appropriate tables, following the defined relationships.
Quality control: Verify the correctness of the data inserted into the database. Run queries to extract the data and compare it with the original documents to ensure the accuracy of the extracted information.
Data querying and analysis: Use SQL language to query the database and retrieve data based on specific criteria.
Updating and maintenance: create scripts or automated procedures for inserting the newly extracted data into the existing database.