System and method for data quality framework and structure

A computerized method implemented via a data quality computer server, comprising:

• storing, in a validation database:
• electronic records connected to a data quality framework for an enterprise, the electronic records including a set of data validation rules, wherein at least one validation rule is associated with a Machine Learning (“ML”) predictive model, and
• metadata defining validation groups that undergo a data quality process together;
• providing, via a data central console platform, validation administration for the data quality framework and an operational dashboard using an interactive graphical display via a distributed communication network, wherein the data central console platform uses the operational dashboard to perform all of:
• (i) failure review, (ii) failure classification, (iii) issue resolution, (iv) re-validation, and (v) case management integration to generate and track tickets to resolve data quality issues;
• retrieving, by a data loading platform from governed datasets, information to be validated;
• receiving, at a computer processor of the data quality computer server, the information to be validated;
• automatically, and in response to receipt of the information to be validated, executing the set of data validation rules on the information to be validated to generate validation results;
• performing further training of the ML predictive model as results become known from processing current information such that the ML predictive model adapts itself to changing event impacts and data quality results;
• storing the validation results;
• performing all of:
• (i) cross-checks, (ii) inventory checks, and (iii) exception trending;
• and
• automatically transmitting an alert message via an automatically established communication link to a communication address, associated with any of an email address, a web account, a smartphone number, a dashboard display, and a chat interface, based on the validation results.

A non-transitory, computer-readable medium storing instructions, that, when executed by a processor, cause the processor to perform a method implemented via a data quality computer server, the method comprising:

• storing, in a validation database:
• electronic records connected to a data quality framework for an enterprise, the electronic records including a set of data validation rules, wherein at least one validation rule is associated with a Machine Learning (“ML”) predictive model, and
• metadata defining validation groups that undergo a data quality process together;
• providing, via a data central console platform, validation administration for the data quality framework and an operational dashboard using an interactive graphical display via a distributed communication network, wherein the data central console platform uses the operational dashboard to perform all of:
• (i) failure review, (ii) failure classification, (iii) issue resolution, (iv) re-validation, and (v) case management integration to generate and track tickets to resolve data quality issues;
• retrieving, by a data loading platform from governed datasets, information to be validated;
• receiving, at a computer processor of the data quality computer server, the information to be validated;
• automatically, and in response to receipt of the information to be validated, executing the set of data validation rules on the information to be validated to generate validation results;
• performing further training of the ML predictive model as results become known from processing current information such that the ML predictive model adapts itself to changing event impacts and data quality results;
• storing the validation results;
• performing all of:
• (i) cross-checks, (ii) inventory checks, and (iii) exception trending;
• and
• automatically transmitting an alert message via an automatically established communication link to a communication address, associated with any of an email address, a web account, a smartphone number, a dashboard display, and a chat interface, based on the validation results.