Transform and Validate Real-Time Data Fast
Keep adding new skills with 10,000+ programs for $239 (usually $399). Save now.
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
Included with
Learn more
Ask Coursera
Recommended experience
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
Details to know
February 2026
1 assignment
See how employees at top companies are mastering in-demand skills
Build your subject-matter expertise
- Learn new concepts from industry experts
- Gain a foundational understanding of a subject or tool
- Develop job-relevant skills with hands-on projects
- Earn a shareable career certificate
There are 3 modules in this course
Imagine youβre 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 youβve learned to drive results and adapt to evolving challenges with confidence.
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
4 videosβ’Total 32 minutes
- Welcome to the Courseβ’5 minutes
- Introduction to Real-Time Dataβ’6 minutes
- Parsing and Exploding Nested JSONβ’11 minutes
- Pivoting for Analyticsβ’11 minutes
2 readingsβ’Total 15 minutes
- Welcome to the Course: Transform and Validate Real-Time Data Fastβ’5 minutes
- Real Time Intelligence in Microsoft Fabricβ’10 minutes
1 peer reviewβ’Total 20 minutes
- Hands-On-Learning: Transform Data into Analytics-Ready Tablesβ’20 minutes
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
4 videosβ’Total 37 minutes
- Benefits of Using PySparkβ’6 minutes
- Integration of Deequ in CI/CD Workflowβ’11 minutes
- Automating Data Quality Checks with CI/CD in Microsoft Fabricβ’10 minutes
- Blocking Low-Quality Mergesβ’11 minutes
1 readingβ’Total 5 minutes
- Optimizing for CI/CD in Microsoft Fabricβ’5 minutes
1 peer reviewβ’Total 30 minutes
- Hands-On-Learning: Automate Data Quality Validation with PySpark and CI/CD Integrationβ’30 minutes
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
5 videosβ’Total 44 minutes
- Connecting Power BI to Fabricβ’6 minutes
- Building Interactive Dashboardsβ’15 minutes
- Optimizing Real-Time Performanceβ’10 minutes
- Optimizing Power BI for Clickstream Analyticsβ’10 minutes
- Course Wrap-up Video β’3 minutes
1 readingβ’Total 5 minutes
- Incremental Refresh and Real-Time Data for Semantic Modelsβ’5 minutes
1 assignmentβ’Total 20 minutes
- Transform and Validate Real-Time Data Fastβ’20 minutes
2 peer reviewsβ’Total 90 minutes
- Hands-On-Learning: Design and Optimize a Real-Time Dashboard in Power BIβ’30 minutes
- Project: End-to-End Real-Time Data Engineering Pipelineβ’60 minutes
Earn a career certificate
Add this credential to your LinkedIn profile, resume, or CV. Share it on social media and in your performance review.
Instructor
Offered by
Explore more from Data Analysis
- Status: Free Trial
Course
- Status: Free Trial
Course
- Status: Free Trial
Course
- Status: Free Trial
Specialization
Why people choose Coursera for their career
Frequently asked questions
To access the course materials, assignments and to earn a Certificate, you will need to purchase the Certificate experience when you enroll in a course. You can try a Free Trial instead, or apply for Financial Aid. The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.
When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile.
Yes. In select learning programs, you can apply for financial aid or a scholarship if you canβt afford the enrollment fee. If fin aid or scholarship is available for your learning program selection, youβll find a link to apply on the description page.
More questions
Financial aid available,
