System and method for determining standardized datasets using optimal features

A non-transitory computer readable medium having stored thereon instructions for causing a processing circuitry to execute a process, the processing comprising:

• clustering a plurality of first datasets with respect to a plurality of tiers, wherein each of the plurality of first datasets includes values representing a plurality of comparable parameters;
• determining an optimal feature for at least one of the plurality of comparable parameters within each tier by applying standardization rules, wherein the standardization rules define a most reoccurring feature for a comparable parameter among the plurality of first datasets, wherein the optimal feature for one of the plurality of comparable parameters within a tier has the most reoccurring feature for the at least one comparable parameter within the tier;
• generating a standardized dataset for each tier, wherein the standardized dataset generated for each tier includes each optimal feature determined for the tier;
• and
• generating a scope of work based on a second dataset and the standardized datasets, wherein the scope of work includes a recommendation to change each of at least one feature represented by the second dataset into a respective optimal feature of a target standardized dataset among the generated standardized datasets.

A system for determining standardized datasets using optimal features, comprising:

• a processing circuitry;
• and
• a memory, the memory containing instructions that, when executed by the processing circuitry, configure the system to:
• cluster a plurality of first datasets with respect to a plurality of tiers, wherein each of the plurality of first datasets includes values representing a plurality of comparable parameters;
• determine an optimal feature for at least one of the plurality of comparable parameters within each tier by applying standardization rules, wherein the standardization rules define a most reoccurring feature for a comparable parameter among the plurality of first datasets, wherein the optimal feature for one of the plurality of comparable parameters within a tier has the most reoccurring feature for the at least one comparable parameter within the tier;
• generate a standardized dataset for each tier, wherein the standardized dataset generated for each tier includes each optimal feature determined for the tier;
• and
• generate a scope of work based on a second dataset and the standardized datasets, wherein the scope of work includes a recommendation to change each of at least one feature represented by the second dataset into a respective optimal feature of a target standardized dataset among the generated standardized datasets.