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.

Transform and Validate Real-Time Data Fast

Transform and Validate Real-Time Data Fast
This course is part of Real-Time, Real Fast: Kafka & Spark for Data Engineers Specialization

Instructor: Tom Themeles
Access provided by Emlyon business school
Recommended experience
What you'll learn
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.
Skills you'll gain
- Performance Tuning
- PySpark
- Data Governance
- Real Time Data
- Dashboard
- CI/CD
- Data Quality
- Business Intelligence
- Data Pipelines
- Data Integrity
- Data Validation
- Data Transformation
- Data Visualization
- Power BI
- Skills section collapsed. Showing 12 of 14 skills.
Details to know

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February 2026
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There are 3 modules in this course
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.
What's included
4 videos2 readings1 peer review
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.
What's included
4 videos1 reading1 peer review
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.
What's included
5 videos1 reading1 assignment2 peer reviews
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