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Transform and Validate Real-Time Data Fast

本课程是 Real-Time, Real Fast: Kafka & Spark for Data Engineers 专项课程的一部分

位教师：Tom Themeles

包含在中

了解更多

3个模块

深入了解一个主题并学习基础知识。

中级等级

推荐体验

5 小时完成

灵活的计划

自行安排学习进度

3个模块

深入了解一个主题并学习基础知识。

中级等级

推荐体验

5 小时完成

灵活的计划

自行安排学习进度

您将学到什么

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.

您将获得的技能

您将学习的工具

要了解的详细信息

可分享的证书

添加到您的领英档案

了解顶级公司的员工如何掌握热门技能

了解关于 Coursera for Business 的更多信息

Petrobras, TATA, Danone, Capgemini, P&G 和 L'Oreal 的徽标

积累特定领域的专业知识

本课程是 Real-Time, Real Fast: Kafka & Spark for Data Engineers 专项课程专项课程的一部分

在注册此课程时，您还会同时注册此专项课程。

向行业专家学习新概念
获得对主题或工具的基础理解
通过实践项目培养工作相关技能
获得可共享的职业证书

该课程共有3个模块

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.

单元详情

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.

涵盖的内容

4个视频2篇阅读材料1次同伴评审

4个视频总计32分钟

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

2篇阅读材料总计15分钟

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

1次同伴评审总计20分钟

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

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.

涵盖的内容

4个视频1篇阅读材料1次同伴评审

4个视频总计37分钟

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

1篇阅读材料总计5分钟

Optimizing for CI/CD in Microsoft Fabric5分钟

1次同伴评审总计30分钟

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

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.