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Transform and Validate Real-Time Data Fast

kurs ist nicht verfügbar in Deutsch (Deutschland)

Wir übersetzen es in weitere Sprachen.

Transform and Validate Real-Time Data Fast

Dieser Kurs ist Teil von Spezialisierung „Real-Time, Real Fast: Kafka & Spark for Data Engineers“

Dozent: Tom Themeles

Bei enthalten

Mehr erfahren

3 Module

Verschaffen Sie sich einen Einblick in ein Thema und lernen Sie die Grundlagen.

Stufe Mittel

Empfohlene Erfahrung

5 Stunden zu vervollständigen

Flexibler Zeitplan

In Ihrem eigenen Lerntempo lernen

3 Module

Verschaffen Sie sich einen Einblick in ein Thema und lernen Sie die Grundlagen.

Stufe Mittel

Empfohlene Erfahrung

5 Stunden zu vervollständigen

Flexibler Zeitplan

In Ihrem eigenen Lerntempo lernen

Was Sie lernen werden

Transform nested and streaming data into analytics-ready tables using programming tools and platforms.
Implement automated data quality checks and integrate these checks into CI/CD pipelines to enforce quality gates.
Build and manage scalable real-time analytics pipelines that block low-quality data and connect curated datasets to Power BI dashboards.

Kompetenzen, die Sie erwerben

Kategorie: Data Processing
Kategorie: Performance Tuning
Kategorie: Data Governance
Kategorie: Real Time Data
Kategorie: Live Streaming
Kategorie: Data Transformation
Kategorie: Data Integrity
Kategorie: Data Validation
Kategorie: CI/CD
Kategorie: Business Intelligence
Kategorie: Data Quality
Kategorie: Data Pipelines
Kategorie: Dashboard Creation

Werkzeuge, die Sie lernen werden

Kategorie: Power BI
Kategorie: PySpark
Kategorie: Dashboard

Wichtige Details

Zertifikat zur Vorlage

Zu Ihrem LinkedIn-Profil hinzufügen

Kürzlich aktualisiert!

Februar 2026

Bewertungen

1 Aufgabe

Unterrichtet in Englisch

91% of learners achieved a positive career outcome

Erfahren Sie, wie Mitarbeiter führender Unternehmen gefragte Kompetenzen erwerben.

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Erweitern Sie Ihre Fachkenntnisse

Dieser Kurs ist Teil der Spezialisierung Spezialisierung „Real-Time, Real Fast: Kafka & Spark for Data Engineers“

Wenn Sie sich für diesen Kurs anmelden, werden Sie auch für diese Spezialisierung angemeldet.

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

Imagine you’re tasked with solving a complex challenge that demands both strategic thinking and hands-on expertise. How do you approach it confidently? In this course, you will be guided through essential concepts and practical applications, empowering you to tackle real-world problems effectively. This course equips you with in-depth knowledge, interactive exercises, and actionable skills designed for immediate impact in your field. By the end of this course, you will have developed a robust understanding of key principles, gained experience with proven strategies, and be prepared to implement solutions in dynamic environments.

Learners should be familiar with basic Python, SQL, basic PySpark, data engineering fundamentals, streaming concepts, and data quality awareness. This course is designed for intermediate data engineers, analytics engineers, and BI professionals who want to build reliable real-time data pipelines with automated quality checks and executive-ready dashboards using Microsoft Fabric, PySpark, and Power BI. By the end of this course, you'll be ready to apply what you’ve learned to drive results and adapt to evolving challenges with confidence.

Moduldetails

Learn to parse, flatten, and reshape real-time data streams into analytics-ready tables. Explore nested clickstream data, explode arrays, and pivot by category for efficient downstream analytics.

Das ist alles enthalten

4 Videos2 Lektüren1 peer review

4 VideosInsgesamt 32 Minuten

Welcome to the Course5 Minuten
Introduction to Real-Time Data6 Minuten
Parsing and Exploding Nested JSON11 Minuten
Pivoting for Analytics11 Minuten

2 LektürenInsgesamt 15 Minuten

Welcome to the Course: Transform and Validate Real-Time Data Fast5 Minuten
Real Time Intelligence in Microsoft Fabric10 Minuten

1 peer reviewInsgesamt 20 Minuten

Hands-On-Learning: Transform Data into Analytics-Ready Tables20 Minuten

In this module, learners will explore how to automate data validation using PyDeequ. They will learn to define and apply data quality constraints, integrate validation seamlessly into CI/CD pipelines, and implement mechanisms to block merges when thresholds are not met. This hands-on module emphasizes building robust, automated systems that safeguard data integrity in production environments.

Das ist alles enthalten

4 Videos1 Lektüre1 peer review

4 VideosInsgesamt 37 Minuten

Benefits of Using PySpark6 Minuten
Integration of Deequ in CI/CD Workflow11 Minuten
Automating Data Quality Checks with CI/CD in Microsoft Fabric10 Minuten
Blocking Low-Quality Merges11 Minuten

1 LektüreInsgesamt 5 Minuten

Optimizing for CI/CD in Microsoft Fabric5 Minuten

1 peer reviewInsgesamt 30 Minuten

Hands-On-Learning: Automate Data Quality Validation with PySpark and CI/CD Integration30 Minuten

This module guides learners through optimizing Microsoft Power BI dashboards with live data connections. It covers real-time data integration, performance strategies such as caching and incremental refresh, and visual design principles.