System and Method for Performing Cross-Platform Big Data Analytics

Abstract

A system and method for performing cross-platform data analytics of advertising campaign information. The system comprises a data sanitizing module for receiving information related to at least one campaign from a plurality of advertising platforms and to produce a normalized dataset having data values that comply with a unified format; a storage and transformation (TS) engine for transforming data values in the normalized dataset into a format defined in a relaxed data schema, thereby resulting with a relaxed dataset, the TS engine is further configured to analyze the relaxed dataset to compute a plurality of campaign measurements of measurable data values included in the relaxed dataset; a data-mart module for storing the relaxed dataset together with the computed campaign measurements; and a management user interface (UI) module for allowing client devices access to data stored in the data-mart module, wherein the data-mart module is optimized for providing an accelerated data for data stored therein.

What is claimed is: 
     
         1 . A system for cross-platform data analytics of information, comprising:
 a memory; and   at least one processor coupled to the memory and configured to:
 aggregate real-time data from a plurality of platforms, wherein the real-time data is related to a common subject from the plurality of platforms, and at least two of the platforms of the plurality of platforms store the real-time data in different formats; 
 produce a normalized dataset having data values that comply with a unified format from the aggregated real-time data; 
 transform the data values in the normalized dataset into a format defined by a relaxed data schema specified by a user thereby resulting in a relaxed dataset, wherein the relaxed data schema comprises a data type, a dimension, a metric definition, a hierarchy of data fields, and an aggregation function for the metric definition; 
 compute a plurality of measurements related to the common subject based on measureable data values included in the relaxed dataset; and 
 output the computed plurality of measurements related to the common subject. 
   
     
     
         2 . The system of  claim 1 , wherein each platform of the plurality of platforms is an ad-serving system of an ad-serving company, a social media website, or a content publisher system. 
     
     
         3 . The system of  claim 1 , wherein the at least one processor further configured to:
 aggregate the measurable data values included in the relaxed dataset.   
     
     
         4 . The system of  claim 1 , wherein to transform the data values in the normalized dataset the at least one processor is further configured to:
 transform the data values in the normalized dataset using a plurality of transformation rules.   
     
     
         5 . The system of  claim 4 , wherein each transformation rule of the plurality of transformation rules is an alteration rule, classification rule, or segmentation rule. 
     
     
         6 . The system of  claim 1 , wherein the plurality of platforms are advertising platforms and the real-time data comprises campaign information, and wherein to compute the plurality of measurements related to the common subject the at least one processor is further configured to compute the plurality of measurements based on at least one predefined campaign objective. 
     
     
         7 . The system of  claim 6 , wherein the at least one processor further configured to determine that the at least one predefined campaign objective is met based on the computed plurality of measurements. 
     
     
         8 . A method for performing cross-platform data analytics of information, comprising:
 aggregating, by at least one processor, real-time data from a plurality of platforms, wherein the real-time data is related to a common subject from the plurality of platforms, and at least two of the platforms of the plurality of platforms store the real-time data in different formats;   producing, by the at least one processor, a normalized dataset having data values that comply with a unified format from the aggregated real-time data;   transforming, by the at least one processor, the data values in the normalized dataset to a format defined by a relaxed data schema specified by a user thereby resulting in a relaxed dataset, wherein the relaxed data schema comprises a data type, a dimension, a metric definition, a hierarchy of data fields, and an aggregation function for the metric definition;   computing, by the at least one processor, a plurality of measurements related to the common subject based on measurable data values included in the relaxed dataset; and   outputting, by the at least one processor, the computed plurality of measurements related to the common subject.   
     
     
         9 . The method of  claim 8 , wherein each platform of the plurality of platforms is an ad-serving system of an ad-serving company, a social media website, or a content publisher. 
     
     
         10 . The method of  claim 8 , further comprising:
 aggregating, by the at least one processor, the measurable data values included in the relaxed dataset.   
     
     
         11 . The method of  claim 8 , wherein the transforming the data values in the normalized dataset further comprises:
 transforming, by the at least one processor, the data values in the normalized dataset using a plurality of transformation rules, wherein each transformation rule of the plurality of transformation rules is an alteration rule, classification rule, or segmentation rule.   
     
     
         12 . The method of  claim 11 , wherein each transformation rule of the plurality of transformation rules is an alteration rule, classification rule, or segmentation rule. 
     
     
         13 . The method of  claim 8 , wherein the plurality of platforms are advertising platforms and the real-time data comprises campaign information, and wherein the computing the plurality of measurements related to the common subject further comprises computing, by the at least one processor, the plurality of measurements based on at least one predefined campaign objective. 
     
     
         14 . The method of  claim 13 , further comprising:
 determining, by the at least one processor, that the at least one predefined campaign objective is met based on the computed plurality of measurements.   
     
     
         15 . A non-transitory computer-readable device having instructions stored thereon that, when executed by at least one computing device, causes the at least one computing device to perform operations comprising:
 aggregating real-time data from a plurality of platforms, wherein the real-time data is related to a common subject from the plurality of platforms, and at least two of the platforms of the plurality of platforms store the real-time data in different formats;   producing a normalized dataset having data values that comply with a unified format from the aggregated real-time data;   transforming the data values in the normalized dataset to a format defined by a relaxed data schema specified by a user thereby resulting in a relaxed dataset, wherein the relaxed data schema comprises a data type, a dimension, a metric definition, a hierarchy of data fields, and an aggregation function for the metric definition;   computing a plurality of measurements related to the common subject based on measurable data values included in the relaxed dataset; and   outputting the computed plurality of measurements related to the common subject.   
     
     
         16 . The non-transitory computer-readable device of  claim 15 , wherein each platform of the plurality of platforms is an ad-serving system of an ad-serving company, a social media website, or a content publisher. 
     
     
         17 . The non-transitory computer-readable device of  claim 15 , the operations further comprising:
 aggregating the measurable data values included in the relaxed dataset.   
     
     
         18 . The non-transitory computer-readable device of  claim 15 , wherein the plurality of platforms are advertising platforms and the real-time data comprises campaign information, and wherein the computing the plurality of measurements related to the common subject further comprises computing, by the at least one processor, the plurality of measurements based on at least one predefined campaign objective. 
     
     
         19 . The non-transitory computer-readable device of  claim 15 , wherein the transforming the data values in the normalized dataset further comprises:
 transforming the data values in the normalized dataset using a plurality of transformation rules, wherein each transformation rule of the plurality of transformation rules is an alteration rule, classification rule, or segmentation rule.   
     
     
         20 . The non-transitory computer-readable device of  claim 19 , wherein each transformation rule of the plurality of transformation rules is an alteration rule, classification rule, or segmentation rule.