Data Engineering for Cybersecurity: Building Robust Data Pipelines, Detection Systems, and Analytics for Modern Security Teams
カートのアイテムが多すぎます
カートに追加できませんでした。
ウィッシュリストに追加できませんでした。
ほしい物リストの削除に失敗しました。
ポッドキャストのフォローに失敗しました
ポッドキャストのフォロー解除に失敗しました
聴き放題対象外タイトルです。Audibleプレミアムプラン登録で、非会員価格の30%OFFで購入できます。
¥1,470 で購入
-
ナレーター:
-
Virtual Voice
-
著者:
-
Adrian Lund
この作品は、デジタルボイスによる朗読を使用しています。
Transform chaotic security logs into robust data pipelines for rapid threat detection and proactive incident response. Perfect for your focused morning commute, this analytical journey rescues overwhelmed technical professionals drowning in fragmented data. Regain control of your hybrid cloud networks by treating security metrics as a first-class product rather than an IT afterthought.
Follow the realistic evolution of a corporate operations center as it transitions from ad hoc spreadsheets to a unified, detection-ready platform. Master the operational realities of modern architectures while bridging the stressful gap between engineering priorities and urgent cyber defense demands.
What you'll discover inside:
• How to architect scalable data flows that seamlessly serve real-time alerts, threat hunting, and compliance reporting.
• Step-by-step strategies for data modeling, storage, ingestion, and enrichment in complex cloud-heavy environments.
• Practical design principles grounded in simulated cybersecurity incidents and daily operational challenges.
• Proven methods to align data engineering teams with security analysts for friction-free, cross-departmental workflows.
• Critical techniques to evaluate operational trade-offs and build systems tailored to your specific organizational maturity.
Stop struggling to answer basic operational questions during critical network breaches and start building data assets that materially improve your reaction speed. Press play to unlock a practical, field-tested mental model that will revolutionize your organization's security posture and elevate your technical career.
©2026 Hidden Voices (P)2026 Hidden Voices