The third quarter of 2024 set a record – and not the good kind. The average weekly cyberattacks per organization rose an incredible 75% YoY and 15% compared to Q2 2024.

As threats become more frequent and sophisticated and the price tag of a data breach continues to increase, up 10% in 2024 according to IBM, ‘it’s only a matter of time’ is the mindset all cybersecurity leaders need to adopt. The current situation demands nothing less.

A few years ago, a Managed Detection and Response (MDR) solution with an outsourced SIEM could have supplied enough protection, but that’s no longer true. Inflexible, unscalable, pieced-together solutions must be replaced, but with what?

Successfully defending the complex infrastructure most organizations have doesn’t require an excessive stack of security tools. Instead, decision-makers should implement the right solutions – ones built to keep pace with evolving threats and growing businesses.

Security data lakes (SDLs) are specifically designed to store and analyze security data and reveal valuable insights that can be used to identify and stop threats in real-time. However, an SDL on its own isn’t a complete solution. A next-gen MDR with a proprietary SDL slashes incident response (IR) times, delivers numerous operational benefits, and is one of the most cost-effective ways to harden security.

A Closer Look at Security Data Lakes

To understand why SDLs are superior in a modern security environment, comparing them to traditional SIEMs is helpful.

SIEMs primarily focus on real-time monitoring, log management, and correlation of security-only data. They require data to be structured and normalized before ingestion, retain data for short periods (usually 90 days or less), and struggle with massive data volumes and growth.

In contrast, SDLs are scalable, ingesting and storing massive amounts of raw, unstructured data from security and non-security sources, creating greater visibility and enabling long-term trend analysis and pattern recognition. They also use advanced analytics, machine learning (ML), and AI capabilities, which unearth insights and expedite real-time threat detection and investigation. Overall, they are more comprehensive and future-proof.

The Impact of SDL on IR Times

Although IBM’s report noted that the average time to identify and contain a breach hit an all-time low – 258 days in 2024 compared to 277 days in 2023 – the cost for shorter breach lifecycles still rose 3.6% YoY. Given the ferocity of attacks and their potentially crippling nature, rapid IR has never been more critical. As every minute counts when containing and mitigating threats, organizations will undoubtedly want to have an SDL on their side.

Here’s a detailed look at how SDLs accelerate IR:

Enhancing Data Collection: Since an SDL can simultaneously ingest data from all sources, no vital information falls through the cracks or goes unnoticed. This ability also produces better visibility, a necessity in complex IT environments.

Optimizing Storage and Analysis: By storing raw data in its native form, SDLs allow flexible querying and analysis without complex transformations.

Enabling Real-time Threat Detection: Advanced analytics and ML algorithms running on the SDL identify patterns and anomalies in real-time, triggering alerts before damage occurs. SDLs also excel at filtering out false positives so security teams can concentrate on genuine threats.

Facilitating Advanced Analytics: ML models trained on the SDL’s repository predict potential threats and suggest proactive measures, amounting to a superpower against relentless AI-generated novel attacks.

Together, these capabilities can dramatically reduce an organization’s mean time to detect (MTTD) and mean time to respond (MTTR) to security incidents, minimizing the impact of threats.

Operational Benefits of MDR with Proprietary SDL vs. Outsourced SIEM

While MDR solutions with proprietary SDLs and those with outsourced SIEMs are geared toward hardening an organization’s security posture, the former offers distinct operational advantages and benefits that make it a wiser choice.

Reduced Latency for Real-Time Monitoring and Response: An MDR with an in-house SDL eliminates the need to route data through external platforms. This reduced latency leads to faster detection and response times; threats are mitigated quicker, and organizations can have peace of mind knowing urgent threats are handled promptly.

Enhanced Data Privacy and Control: A proprietary SDL gives companies tighter control over data processing, storage locations, and privacy and security policies, providing more safety than third-party platforms. Managing data in strictly controlled environments with reliable encryption and access protocols is especially important for sensitive industries like finance and healthcare, which must adhere to rigid data security and compliance laws.

Optimized Data Retention Policies for Compliance: Companies with their own SDL can establish flexible, compliance-friendly data retention policies without the constraints of third-party SIEMs. This allows for long-term data storage options that align with GDPR, HIPAA, or CCPA requirements and complete audit trails, lessening compliance risks and potential penalties.

End-to-End Ownership of the Security Stack: Complete ownership of the security stack, from data ingestion to alerting, ensures components are optimized and work cohesively, resulting in a seamless experience, reduced errors, and better threat detection. Unlike a solution built with multiple third-party tools, a fully integrated single-source stack produces smoother workflows, higher data integrity, and streamlined responses, strengthening a company’s overall security posture.

Faster, Tailored Threat Detection with Rich Data Correlation: A proprietary SDL offers customized log ingestion, processing, and real-time correlation tailored to meet each organization’s needs. This approach creates unique, company-specific data correlations that improve detection speed and alert accuracy, reducing alert fatigue so teams spend time investigating genuine threats.

Full Data Visibility and Transparent Investigations: Proprietary SDLs store raw logs and historical data without external limitations, supplying access to past and present information. Full transparency enables organizations to conduct in-depth investigations. Comprehensive visibility supports forensic analyses and retrospective threat hunting and strengthens compliance by ensuring data is complete and always accessible.

Cost-Effectiveness of MDRs with Proprietary SDLs

In addition to its operational advantages, an MDR with a built-in proprietary SDL presents several cost-saving opportunities compared to an MDR with an outsourced SIEM:

Scalability and Flexibility: An SDL-powered MDR solution easily adapts to changing business needs without requiring costly infrastructure upgrades or new system implementations.

Efficient Data Management: Centralizing all security data reduces the need for multiple tools and integrations, leading to lower operational and IT costs.

Improved Threat Detection: Faster threat identification and mitigation reduces downtime and the financial impact of a breach.

Reactive Security is a Costly Mistake

A Forrester report found that after experiencing a breach, 42% of organizations increased their spending on IR technologies when personal data was compromised, and 46% did so when corporate data was affected. Those companies incurred the cost of new tech solutions and those associated with the breach. Learn from their mistakes. Companies relying on solutions with outsourced SIEMs can take the wait-and-see reactive approach, incurring high costs, or proactively adopt an MDR solution with a built-in SDL. The latter is a cost-effective, comprehensive solution that accelerates IR, mitigates financial risks, and enhances operational efficiency. The choice seems clear.