In a world where business decisions happen in seconds, is your data fast enough? Traditional batch processing creates a critical "insight lag," forcing you to react to yesterday's news. This hands-on course empowers you to design, build, and optimize high-speed data pipelines that serve as the nervous system of modern business. Working in a ready-to-use cloud environment with industry-standard Apache Spark, you will master the complete lifecycle of real-time data engineering. Through practical, real-world case studies from e-commerce, IoT, and FinTech, you'll learn to build live operational dashboards, apply window functions to analyze trends over time, and design a sophisticated, real-time fraud detection engine. You will leave this course with the skills to transform massive, high-speed data streams into immediate, actionable business value and become the go-to expert for creating low-latency solutions that give companies their competitive edge.
Process & Analyze Real-Time Data Fast
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Process & Analyze Real-Time Data Fast
Dieser Kurs ist Teil von Spezialisierung „Real-Time, Real Fast: Kafka & Spark for Data Engineers“
Dozenten: Jairo Sanchez
Bei enthalten
Empfohlene Erfahrung
Was Sie lernen werden
Architect a streaming data solution by differentiating between batch, micro-batch, and streaming patterns to solve a specific business problem.
Develop real-time analytics pipelines using window functions and watermarking to aggregate and analyze streaming data.
Optimize a production streaming application by diagnosing performance bottlenecks like data skew and implementing mitigation techniques.
Kompetenzen, die Sie erwerben
- Kategorie: Data Pipelines
- Kategorie: Real Time Data
- Kategorie: Data Processing
- Kategorie: Data Analysis
- Kategorie: Trend Analysis
- Kategorie: Internet Of Things
- Kategorie: Performance Analysis
- Kategorie: Anomaly Detection
- Kategorie: Big Data
- Kategorie: Performance Tuning
Werkzeuge, die Sie lernen werden
- Kategorie: Operational Databases
- Kategorie: Databricks
- Kategorie: Dashboard
- Kategorie: Apache Spark
- Kategorie: Fraud detection
- Kategorie: PySpark
Wichtige Details
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Februar 2026
1 Aufgabe
Erfahren Sie, wie Mitarbeiter führender Unternehmen gefragte Kompetenzen erwerben.
Erweitern Sie Ihre Fachkenntnisse
- Lernen Sie neue Konzepte von Branchenexperten
- Gewinnen Sie ein Grundverständnis bestimmter Themen oder Tools
- Erwerben Sie berufsrelevante Kompetenzen durch praktische Projekte
- Erwerben Sie ein Berufszertifikat zur Vorlage
In diesem Kurs gibt es 3 Module
In this module, learner will step into the role of a data analyst at a fast-growing e-commerce company. Learner will tackle their biggest challenge: replacing slow, nightly reports with a live dashboard to monitor a critical flash sale. Learner will master the fundamentals of stream processing and learn why real-time data is a competitive necessity. This module demonstrates these concepts using Apache Spark.
Das ist alles enthalten
4 Videos2 Lektüren1 peer review
As an IoT Engineer for a smart city initiative, you are responsible for making sense of hundreds of traffic sensors generating chaotic, often delayed data. In this module, you will explore the critical distinction between event time and processing time, master stateful analytics using window functions, and apply watermarking to handle late-arriving data. By the end, you'll be able to design robust real-time pipelines that reveal trends and actionable insights from complex, continuous streams.
Das ist alles enthalten
3 Videos1 Lektüre1 peer review
This module will guide you through identifying and resolving performance bottlenecks using techniques like salting, and then applying stateful analytics to build a prototype for real-time fraud detection. In your role as a Platform Engineer at a fast-growing FinTech company, you are challenged with stabilizing a critical payment pipeline crippled by data skew and tasked with defending against rapidly evolving fraud threats. By the end, you will have mastered the skills needed to optimize and operationalize production-grade streaming applications in high-stakes environments.
Das ist alles enthalten
4 Videos1 Lektüre1 Aufgabe2 peer reviews
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