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Managing quality of data is a very important part of data management in organization (Data Governance). This has a direct impact, first of all, on the correctness of all analyzes performed in the company, in every business unit.

Based on type of data, data cleaning can be split into:

Data integrity: postal addresses, names and surnames, company names, e-mail addresses, telephone numbers, data identifying persons and companies, areas e.g. where soft pattern techniques is using to matching, reference dictionaries and regular expressions

Verification of financial data consisting in the implementation of solutions checking: compliance of numbers - amounts, stored in databases of various systems with the result calculated by an additional algorithm

WE WILL RUN COMPLETE DATA VERIFICATION PROCESS

WE WILL IDENTIFY DATA SOURCES WRONG QUALITY AND ADVISE HOW TO IMPROVE THEM

WE WILL CREATE AND IMPLEMENT RULES FOR DATA QUALITY IMPROVEMENT

We will implement data quality metrics