Abstract
<title>Abstract</title> <p>Enterprise CRM systems use distributed cloud storage to store redundant records and improve the reliability of analytics. Repetitive deduplication can cause costly latency on cloud warehouses, or conversely, poor reliability. The paper notes the significance of using a dataset of 660K+ records and implementing Workflow-Orchestrated Adaptive Survivorship Scoring (WOASS) technique, which involves using Google BigQuery parallel processing and Apache Airflow orchestration, to achieve near-instant resolution to entities. Learned the importance of weights, a survivorship scoring scheme that's based on recency and source authority. Frequency heuristics and a composite attribute similarity function are both utilized in this context. A governance layer that can be monitored from an angle without any breaches in control. The analysis compared 97 CRM records with a database made up of 662,763 CRM records by 20 respondents from BigQuery. So, the correct number is 96. The recall revealed that 8% of the drivers hadn't yet achieved an F1 score. This puts the total count at 970. The total range was between 4% and 18. The increase is mainly due to overrule and ML, resulting in a gap of 8 percentage points between the baselines. The span of 3 seconds (4. ). The index of data quality is 94% (with a 7-point speed bump), and the audit coverage is 97%. The statistical range is computed at p 0. Just one thing.</p>