This is the code in my aml_solution_db_pipeline.py file. Here I have added 2 more violations to tehe already existing ones, that was my first task to do. and the file when I run gives me the sstaging table data with violations as the output. the code is writting only for the staging data. now I have 2 tasks to do. first to add few more violations and document them. next is to create target tables from staging tables. Have also attached screenshots of my output sourse table for 1, my python value generator file, image of how metadata looks like. In DL_SPEC, data lineage table(Here i have sourse and target tables and their fields),And the source data type and see the goal is that need code to generate target tables, so pls provide
Based on your screenshots, I can see you're working on an AML (Anti-Money Laundering) solution that generates staging tables with data violations. Now you need to add more violations and create target tables from the staging data according to the data lineage specifications.
Let's address both tasks:
Looking at your current code, you already have these violation types:
datatype: Incorrect data type violationsout_of_range: Values outside acceptable rangesnumeric_constraint: Numeric value constraint violationsinconsistent_date: Date format inconsistenciesLet's add more violation types that would be relevant for AML monitoring:
I've added five new violation types to enhance your AML solution:
null_value: Introduces NULL values in fields that should not be NULL
pattern_mismatch: Values not matching expected patterns/formats
referential_integrity: Foreign key violations
duplicate_value: Unexpected duplicate values
length_violation: String length violations
I've implemented a target table creation process that:
Run the script to:
Output files:
csv_no_vio/[table_name].csvcsv_with_vio/[table_name].csvcsv_target/[table_name].csvaml_database.db, aml_database_vio.db, aml_database_target.dbcsv_with_vio/violation_log.docx, csv_target/pipeline_documentation.docxThe code implements the data lineage mappings shown in your Excel sheets, where:
This implementation ensures that your target tables accurately reflect the data lineage specifications while maintaining the data quality checks through the violation system.
To configure the generation, complete these steps:
adding a data documentation screenshot for your reference, go through it and attempt again to write optimized clean code that will generate target tables
Looking at your data documentation screenshot, I can see the detailed column descriptions and metadata. Let me create a more optimized and clean solution focused specifically on generating target tables from your staging data based on the data lineage specifications.
TargetTableGenerator class encapsulates all functionalitycsv_with_vio folderRun the main script:
python target_table_generator.pyCheck outputs:
csv_target/[table_name].csvaml_target_tables.dbcsv_target/generation_summary.jsoncsv_target/validation_report.jsonBased on your data lineage, this will generate:
CUST_CREDIT_RTNGCUST_MKT_SERVEDCUST_PRODUCTCUST_SUPPLEMENTAL_ATTRCUST_ACCTCUST_ACCT_ROLECNTRL_CUSTCORP_ACTNCUSTEach table will have proper data type conversions and transformations applied according to the specifications in your documentation.
To configure the generation, complete these steps:
adding a data documentation screenshot for your reference, go through it and attempt again to write optimized clean code that will generate target tables