Database Event Validation for Card Transaction Replication
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Conventional systems for card-based payment transactions face issues with secure and accurate data transmission and storage due to rudimentary data quality checks, leading to data gaps and inefficiencies in real-time recording and reporting.
Innovation Solution
A database replication system that validates database events based on quantities and event identifier sequencing to ensure completeness and ordering, replicating data only after validation, thereby preventing data corruption and improving accuracy and efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional systems utilize rudimentary data quality checks when merging/replicating data, then the data replication process is simple and fast, but the data accuracy and completeness deteriorate resulting in significant data gaps
Solution Approach 1:
The system performs preliminary validation of data completeness and sequencing before data replication occurs. Validation functions check database events for completeness and proper sequencing prior to merging, preventing data gaps from occurring in the first place rather than detecting them after replication.
Solution Approach 2:
The system implements feedback mechanisms where validation results from checking data completeness and sequencing are used to control the replication process. If validation fails, the system identifies and corrects data gaps before proceeding with replication, ensuring accurate data transfer.
2Reliability
If conventional systems perform data error correction processes to fill in data gaps, then data accuracy improves, but the processing time and computing resources increase significantly
Solution Approach 1:
The system performs preliminary validation to identify potential data gaps and sequencing issues before replication occurs. By detecting and addressing completeness and ordering problems in advance, the system eliminates the need for time-consuming post-replication correction processes.
Solution Approach 2:
The validation functions quickly assess data completeness and sequencing using efficient algorithms that check critical parameters without performing exhaustive analysis. This allows the system to rapidly identify and skip over valid data while focusing correction efforts only on problematic areas.
3Productivity
If conventional systems utilize simple row count verification for data quality checks, then the validation process is efficient, but the measurement precision of data quality deteriorates
Solution Approach 1:
The system applies different validation strategies to different aspects of data quality. Rather than using a single uniform check, it performs localized validation functions that assess specific critical parameters such as data completeness and sequencing independently, providing precise verification of data quality without excessive overall complexity.
Solution Approach 2:
The system changes validation parameters dynamically based on the specific replication context. Validation functions adjust which data attributes are checked and at what depth based on the type of data being replicated and the identified quality issues, optimizing both speed and precision for each validation scenario.
Data Source
AI summary
This disclosure describes methods, non-transitory computer readable storage media, and systems that utilize a plurality of data validation processes to merge or replicate data across databases for downstream operations. For example, in response to a request to merge data from one or more source servers to one or more destination servers, a disclosed system determines database events to merge based on a plurality of database tables accessed in connection with a card account transaction. The disclosed system validates subsets of database events for the accessed database tables based on the quantities and event identifier sequencing of the database events. Additionally, the disclosed system replicates the database events from the source servers to the destination servers in response to validating the completeness and ordering of the database events for the card account transaction.