Data trend analysis based on real-time data aggregation

A non-transitory computer-readable medium that stores executable instructions for analyzing a data trend, when executed by one or more processors, cause the one or more processors to:

• store a plurality of transaction records, each transaction record comprising at least a merchant ID, a transaction amount, and a time stamp, the merchant ID being associated with a location, each transaction record being associated with at least one user;
• receive the plurality of transaction records;
• categorize the plurality of transaction records based on their associated merchant IDs to create different groups of the plurality of transaction records, wherein each group of the plurality of transaction records is associated with at least one of the merchant IDs;
• for each of the merchant IDs in a first group of the plurality of transaction records, determine a number of the plurality of transaction records that are associated with the time stamp within a pre-determined time period;
• for each of the merchant IDs in the first group of the plurality of transaction records, detect a trend of transaction bursts when the determined number of the plurality of transaction records exceeds a pre-determined threshold within the pre-determined time period;
• identify at least a first merchant ID in the first group of the plurality of transaction records with the determined number of transaction records that exceeds the pre-determined threshold;
• identify a first location associated with the first merchant ID;
• generate a first trending notification indicating that the trend of transaction bursts occurs for the first merchant ID in the first location within the pre-determined time period;
• identify a first set of users that are associated with the first location;
• identify a subset of the first set of users associated at least one transaction record identifying the first merchant ID;
• and
• send the first trending notification to the subset of the first set of users.

A method for analyzing a data trend, comprising:

• storing a plurality of transaction records, each transaction record comprising at least a merchant ID, a transaction amount, and a time stamp, the merchant ID being associated with a location, each transaction record being associated with at least one user;
• receiving the plurality of transaction records;
• categorizing the plurality of transaction records based on their associated merchant IDs to create different groups of the plurality of transaction records, wherein each group of the plurality of transaction records is associated with at least one of the merchant IDs;
• for each of the merchant IDs in a first group of the plurality of transaction records, determine a number of the plurality of transaction records that are associated with the time stamp within a pre-determined time period;
• for each of the merchant IDs in the first group of the plurality of transaction records, detect a trend of transaction bursts when the determined number of the plurality of transaction records exceeds a pre-determined threshold within the pre-determined time period;
• identifying at least a first merchant ID in the first group of the plurality of transaction records with the determined number of transaction records that exceeds the pre-determined threshold;
• identifying a first location associated with the first merchant ID;
• generating a first trending notification indicating that the trend of transaction bursts occurs for the first merchant ID in the first location within the pre-determined time period;
• identifying a first set of users that are associated with the first location;
• identifying a subset of the first set of users associated with at least one transaction record identifying the first merchant ID;
• and
• sending the first trending notification to the subset of the first set of users.