Data Quality at the Core of PredictHQ
PredictHQ prioritizes data quality in its data pipeline to deliver verified, forecast-grade data to its users. Unlike raw event APIs that are secondary products for ticketing sites, PredictHQ focuses on ensuring the accuracy and reliability of its data. With over 1,000 machine learning models in place, the platform guarantees high-quality data, eliminating the need for users to worry about data accuracy.
The Data Aggregation Process
PredictHQ aggregates events from a wide range of public and proprietary data sources, ensuring depth and diversity in its data pool. By sourcing events from multiple APIs and deleting up to 45% of inaccurate or spam events, PredictHQ provides trustworthy and enriched event information. This comprehensive aggregation process enhances the quality of forecast models and helps in decision-making for businesses.
Standardizing Data for Consistency
Global coverage of millions of events demands standardization, which PredictHQ accomplishes by ensuring that every event conforms to the same format. With 18+ event categories all standardized, models can quickly understand the combined impact of various events. This standardization simplifies data processing and analysis, enabling efficient utilization of event data for forecasting and planning purposes.
De-Duping for Accurate Insights
Detecting and removing duplicate events is crucial to prevent distorted forecasting and inaccurate models. PredictHQ employs a sophisticated system to automatically identify and eliminate duplicate events, consolidating and verifying them into a single reliable listing. By eliminating duplicate entries, the platform ensures that forecasting models are based on accurate, non-repetitive event data.
Filtering to Remove Irrelevant Data
To maintain the integrity of its data, PredictHQ filters out spam events and irrelevant data that may skew forecasting results. By ingesting over 500,000 new event records monthly and quickly identifying and removing spam events and duplicates, PredictHQ guarantees that users access only high-quality, impactful event information. This filtering process enhances the accuracy and reliability of forecasting models.
Driving Event Data Quality with QSPD
PredictHQ's rigorous verification and enrichment processes, powered by the Quality, Standardization, Processing, and Deduplication (QSPD) framework, ensure that event data meets the highest quality standards. By leveraging a knowledge graph and entity system, the platform validates details and adds intelligence layers to each event, enhancing the overall accuracy and value of the data provided to users.