Method and system for artificial intelligence-driven data migration and standardization across software platforms

A computer-implemented method, comprising:

• receiving, by at least one processor, a data migration request to migrate data from a particular data source to a plurality of data sources,
• data migration request comprises a plurality of selected data points to be migrated from the particular data source to the plurality of data sources;
• wherein the data is of at least one data type associated with the plurality of data sources;
• wherein the particular source is at least one database or at least one data platform;
• wherein each selected data point of the plurality of selected data points is defined to have at least one first parameter,
• determining, by the at least one processor, at least one second parameter associated with at least one candidate data point of a plurality of candidate data points within the plurality of selected data points based on at least one constraint of the data migration request,
• wherein the at least one second parameter is determined based on a similarity score between the at least one candidate data point and the plurality of selected data points,
• wherein the data migration request further specifies a target schema associated with the at least one second data source;
• and
• utilizing, by the at least one processor, a trained artificial intelligence module to;
• identify a plurality of matching data points from the plurality of candidate data points based at least in part on the at least one second parameter,
• generate, for each identified matching data point and prior to migration, a confidence score for each of the plurality of matching data points,
• prioritize the identified plurality of matching data points based on a ranking algorithm associated with the confidence score,
• determine, based on the target schema associated with the at least one second data source, whether data conversion is required for the prioritized plurality of matching data points during migration from the first data source to the at least one second data source,
• transform the data associated with the prioritized plurality of matching data points to conform with the target schema prior to migration by recalibrating data formats and aligning fields when data conversion is required, and
• automatically migrate the data to the plurality of data sources,
• wherein the trained data migration artificial intelligence module is configured to comprise a plurality of relationships between:
• at least one occurrence of the data within the plurality of data sources,
• at least one chronological path of data entry of the data associated with the at least one occurrence of the data within the plurality of data sources,
• a rate of the data entry of the data associated with the at least one occurrence of the data within the plurality of data sources,
• the at least one first parameter,
• the at least one second parameter, and
• the at least one constraint of the data migration request;
• wherein the trained data migration artificial intelligence module omits at least one step of a data migration process for subsequent data migration requests;
• wherein the trained data migration artificial intelligence module is configured to automatically reconcile schema differences, standardize data formats, and prevent data truncation during migration to eliminate redundant entry of identical data points into multiple databases, thereby reducing error rates, improving access to migrated data, and minimizing opportunity costs in terms of time and resources during migration;
• providing, by the at least one processor, at least one real-time report on the status of the data migration request of the plurality of selected data points, wherein the at least one real-time report comprises anticipated timing of trigger events required for subsequent migration of the plurality of selected data points to the plurality of data sources;
• and
• organizing, by the at least one processor, the plurality of selected points set based on a set of predetermined parameters.

A system comprising:

• a non-transient computer memory, storing software instructions;
• at least one or more components of at least one processor configured to execute the software instructions that cause the at least one processor to perform steps to:
• receive a data migration request to migrate data from a first data source to at least one second data source;
• wherein the data migration request comprises a plurality of selected data points to be migrated from the first data source to the at least one second data source;
• wherein the data is of at least one data type associated with the at least one second data source;
• wherein the first data source is at least one database or at least one data platform;
• wherein each selected data point of the plurality of selected data points is defined to have at least one first parameter;
• determine at least one second parameter associated with at least one candidate data point of a plurality of candidate data points associated with the first data source based at least in part on:
• at least one constraint of the data migration request, and
• the at least one first parameter associated with each selected data point of the plurality of selected data points associated with the at least one second data source;
• wherein the at least one second parameter is determined based on a similarity score between the at least one candidate data point and the plurality of selected data points,
• wherein the data migration request further specifies a target schema associated with the at least one second data source;
• utilize a trained data migration artificial intelligence module to:
• identify a plurality of matching data points from the plurality of candidate data points based at least in part on the at least one second parameter,
• generate, for each identified matching data point and prior to migration, a confidence score for each of the plurality of matching data points,
• prioritize the identified plurality of matching data points based on a ranking algorithm associated with the confidence score,
• determine, based on the target schema associated with the at least one second data source, whether data conversion is required for the prioritized plurality of matching data points during migration from the first data source to the at least one second data source,
• transform the data associated with the prioritized plurality of matching data points to conform with the target schema prior to migration by recalibrating data formats and aligning fields when data conversion is required, and
• automatically migrate the data associated with the plurality of matching data points to the at least one second source;
• wherein the trained data migration artificial intelligence module is configured to automatically reconcile schema differences, standardize data formats, and prevent data truncation during migration to eliminate redundant entry of identical data points into multiple databases, thereby reducing error rates, improving access to migrated data, and minimizing opportunity costs in terms of time and resources during migration;
• and
• retrain the trained data migration artificial intelligence module to form a retrained data migration module based at least in part on a plurality of:
• at least one occurrence of the data within the at least one second data source,
• at least one chronological path of data entry of the data associated with the at least one occurrence of the data within the at least one second data source,
• a rate of the data entry of the data associated with the at least one occurrence of the data within the at least one second data source,
• the at least one first parameter,
• the at least one second parameter, and
• the at least one constraint of the data migration request.