Building an Intelligent Alerting System for Data Monitoring: Lessons from Energy, Oil and Gas

The Real-Time Risk of Inaction

In fast-moving industries like oil, gas, and energy, data loses value by the minute. A pricing update delayed by even a few hours can mean missed trading windows, skewed benchmarks, or compliance violations. Traditional data harvesting systems that monitor passively or alert reactively no longer meet the speed and scale demands of today’s enterprises.

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This problem is compounded by the nature of data today — nearly 80% of global data is now unstructured, and it's growing three times faster than structured data. Yet many enterprises lack the tools to monitor or manage this influx effectively.

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To stay competitive and compliant, organisations need intelligent alerting systems embedded into their data pipelines - solutions that detect what’s wrong, understand why it matters, and notify the right team, fast.

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Merit Data & Technology’s approach stands out by embedding a hybrid intelligent alerting framework directly into large-scale, real-time data harvesting pipelines—enabling anomaly detection across structured, semi-structured, and unstructured sources, with minimal human intervention.

The Limits of Traditional Monitoring

Traditional monitoring systems often focus on surface-level checks - they catch obvious failures but miss deeper, real-time data quality issues that directly affect business outcomes.

What they often miss:

• Duplicate records slipping through in high-frequency streams
• Timestamp mismatches across global sources
• Schema drift or field-level inconsistencies in dynamic datasets
• Sudden drops or spikes in data volume that go un-contextualised

Even when alerts are generated, they’re often too noisy or generic to drive action. Over-alerting is just as risky: when every minor variation triggers a warning, real issues get lost in the noise.

What’s needed instead is:

• Proactive alerting, not reactive clean-up
• Contextual insights, not raw flags
• Actionable intelligence, not just status notifications

What Intelligent Alerting Really Means

Merit’s intelligent alerting framework is deeply integrated into its ETL (Extract, Transform, Load) pipeline. It combines:

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Rules-based alerts: Detect known issues like schema changes, missing values, and format inconsistencies

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ML-based anomaly detection: Identify novel disruptions such as volume anomalies, pattern drift, unexpected null values, duplicate spikes, timestamp irregularities, and sudden shifts in field distributions - even when the data structure remains unchanged.

Alerts are:

• Generated in real time
• Prioritised based on business impact: Alerts are ranked according to the severity of downstream effects - such as disruptions to high-priority KPIs, automation workflows, or real-time decision systems
• Routed via ITSM tools and downstream systems: Alerts are integrated with incident management platforms like ServiceNow or Jira Service Management, which then trigger notifications through APIs, email, or collaboration tools like Slack or MS Teams - ensuring the right stakeholders are alerted through the right channels

This hybrid model delivers not just alerting - but real-time, intelligent triage across complex data harvesting environments.

Case Study: Monitoring Pricing Intelligence at Scale

A global intelligence provider serving energy and commodities markets turned to Merit to monitor high-frequency data operations across:

• 800+ data sources
• Over a billion records daily
• Multiple time zones and structured formats

The Challenge:

• Detect issues with scrapers, API sources, or content structure in real time
• Flag anomalies in pricing and volume data across geographies
• Ensure uninterrupted, high-quality data flow for pricing intelligence

The Solution:

• A cloud-deployable, multi-threaded Python scraping infrastructure
• Embedded rules and ML-based alerts within ETL flows
• Real-time delta differencing and data stitching
• Alerts routed via automated workflows and team dashboards

The Outcome:

• 99.8%+ data accuracy, consistently maintained
• 30% cost reduction in operations due to fewer manual checks
• 50% faster price update cycles
• High scalability with low engineering overhead

What Makes Merit’s Alerting System Different

Unlike generic tools that treat monitoring as an add-on, Merit’s alerting capabilities are:

• Built-in by design, not bolted on
• Domain-specific, with logic configurable based on industry needs and dataset
• Cross-platform compatible, deployable on cloud or on-premise
• Capable of handling structured, semi-structured, and unstructured sources—from APIs to dynamic websites and scanned documents

This depth enables Merit to offer:

• Real-time anomaly detection across entire pipelines
• Alert customisation down to field-level logic
• Seamless integration with existing BI, ETL, or orchestration systems

The Takeaway: Real-Time Monitoring That Understands Your Data

Involatile, high-stakes sectors like oil, gas, and energy, delays in data insight mean lost revenue, compliance exposure, and missed opportunities. Basic alerts are no longer enough.

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The global datasphere is expected to reach ~175 ZB by 2025, with around 80% being unstructured. Monitoring systems must evolve to meet the challenge.

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Merit’s intelligent alerting system delivers targeted, actionable, and scalable monitoring - purpose-built for the data demands of modern enterprises.

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Let’s explore how our frameworks can help you:

• Detect anomalies faster
• Improve data quality and trust
• Reduce firefighting and manual triage
• Enable high-confidence decisions across the enterprise

Reach out to schedule a pilot or speak with our data monitoring specialists.