Merit’s real-time data harvesting solutions empower energy and commodity markets with 24x7, high-frequency insights that replace slow, outdated batch processing.
In 2024 and 2025, global events have underscored a harsh reality: energy and commodity markets don’t sleep. Whether it's OPEC+ policy changes made overnight, extreme weather disrupting LNG routes, or geopolitical unrest reshaping oil flows, price movements unfold in real time across geographies and time zones.
For companies operating in these high-stakes sectors, relying on traditional batch-based data collection is no longer viable. By the time the data is processed, the market has already moved on – creating risk, inefficiency, and missed opportunities.
To compete in this environment, energy and commodity intelligence providers need always-on data harvesting frameworks: systems that have to be built for speed, scale, and accuracy.
This is precisely what Merit’s Data Sourcing & Aggregation solutions are built to deliver.
Merit’s solutions are purpose-built to automate and streamline the following:
1. Smart Data Sourcing & Aggregation: Combines GenAI-powered classification with high-frequency scraping and robust ETL pipelines that apply complex - even dynamic - data quality rules in real time. This ensures only the most reliable, structured data enters the downstream workflows, regardless of source variability.
2. Streamlined Data Engineering: Leverages proven technologies like Apache Spark Streaming, Kafka, and scalable microservices to process, enrich, and stream high-velocity datasets. These engineering pipelines can be embedded directly into real-time decision-making systems or business process workflows for immediate insights and decision making.
3. AI-Powered Intelligence Platforms: Enables the setup of advanced analytics and machine learning systems that can monitor market conditions, detect anomalies, and surface predictive signals — all while aligning with the unique regulatory and operational needs of energy and commodity markets.
Together, these layers form the backbone of Merit’s real-time data harvesting architecture — engineered for performance at scale, and adaptable to the demands of fast-moving global markets. Whether deployed on cloud or on-premise, the system can handle vast volumes of structured and unstructured data from diverse sources, with minimal latency and high reliability.
Its modular design ensures flexibility across market segments, while integrated capabilities like high-frequency scraping, automated quality checks, and anomaly detection make it possible to deliver clean, analysis-ready data in near real time. The result: business and technical teams are equipped with timely, trusted intelligence - enabling proactive responses to market changes as they unfold.
While batch pipelines have long been a staple in enterprise data architectures, their limitations become increasingly evident in sectors where pricing volatility, global operations, and time-sensitive intelligence matter.
In markets that operate 24x7, the gap between data collection and decision-making can become a liability. Traditional batch systems, which ingest or process data on fixed schedules (such as hourly or daily), simply weren’t built for the always-on nature of today’s commodity ecosystems.
Latency Is the Real Bottleneck: Batch jobs introduce delay by design. Even if data quality is high, it’s often delivered too late to influence fast-moving decisions — such as price adjustments, supply chain negotiations, or advisory recommendations. When time is of the essence, latency erodes competitive edge.
Blind Spots from Fixed Schedules: Between one batch run and the next, markets may have shifted. In volatile commodity environments, intraday fluctuations, news events, or regulatory announcements may go unrecorded - creating blind spots in analysis. The result? Missed opportunities or misinformed actions.
Compliance Readiness Suffers: While real-time compliance is rarely mandated, slow data availability can still delay internal reporting and reduce audit readiness. Teams may struggle to collate and verify data in time for submission cycles, especially when relying on lagging batch outputs for compliance dashboards.
Manual Overhead Increases Without Automation: Both batch and real-time systems can require manual intervention - but the impact is amplified in batch contexts where automation and dynamic data validation are often missing. This leads to:
Merit’s solution replaces static batches with a resilient, continuous data pipeline. At its core are high-frequency Python/Scrapy scrapers running in parallel, enabling 24/7 extraction from hundreds of sites. The system is designed to ingest data at scale - from millions to even billions of records daily - across hundreds of global sources, depending on compute resources. Key features include:
By addressing each batch-era weakness, Merit’s framework delivers actionable market data in near real time.
One of the world’s leading industry intelligence organisations in the oil, natural gas, and commodities sector turned to Merit to modernise its pricing data infrastructure. The client provides pricing assessments, trends forecasting, and consulting services to clients in over 100 countries - their insights are foundational to both physical trade and the benchmarking of financial derivatives.
But with price signals shifting rapidly across time zones, their legacy data harvesting systems — which relied on batch-mode collection - were no longer adequate. They needed a solution that could scale across 800+ online sources, collect and process over a billion records per day, and deliver data in near real time to meet global market expectations.
The Merit Solution: Merit deployed a Python-led scraper solution powered by a self-driven ETL framework that could run multiple configurations in parallel - built for resilience, scale, and speed.
In today’s volatile energy and commodities landscape, access to accurate, up-to-the-minute pricing and market data is business-critical.
Merit’s real-time data harvesting solution delivers a future-ready approach: one that combines
Ready to shift from reactive reporting to proactive decision-making? Talk to Merit about building a real-time data harvesting strategy that matches the speed of your market.
