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Il y a 3 modules dans ce cours
Master the critical skills for ensuring data reliability and building self-healing data systems. This course transforms your approach to data quality from reactive firefighting to proactive engineering driven reliability.
This Short Course was created to help data management and engineering professionals accomplish systematic data quality assurance and error automation at enterprise scale.
By completing this course, you'll be able to implement quantitative data quality measurements, establish monitoring systems that catch degradation trends before they impact business operations, and build intelligent SQL routines that automatically recover from data pipeline failures.
By the end of this course, you will be able to:
• Apply calculations to measure key data quality dimensions
• Evaluate quality key performance indicators over time and recommend remediation
• Create an automated SQL routine to handle and reprocess data errors.
This course is unique because it blends quantitative data quality methods with practical automation engineering, enabling you to build self-healing data systems that maintain measurable quality standards at scale.
To be successful in this course, you should have a background in SQL, data pipeline concepts, and basic data engineering principles.
Learners will master the quantitative measurement of critical data quality dimensions through systematic calculation methods that provide objective assessment of data reliability.
Inclus
3 vidéos1 lecture2 devoirs
Afficher les informations sur le contenu du module
3 vidéos•Total 16 minutes
Core Data Quality Dimensions and Mathematical Foundations•7 minutes
Advanced Quality Calculation Techniques for Enterprise Systems•5 minutes
Building Quality Calculation Dashboards in SQL•4 minutes
1 lecture•Total 10 minutes
Implementing Quality Calculations in SQL and Python•10 minutes
2 devoirs•Total 20 minutes
Implementing Quality Metrics for E-commerce Product Database•15 minutes
Data Quality Dimension Calculations Knowledge Check•5 minutes
Module 2: Core Application - Quality KPI Evaluation and Remediation
Module 2•1 heure à terminer
Détails du module
Learners will master the evaluation of quality key performance indicators over time and develop actionable remediation strategies that prevent quality degradation before it impacts business operations.
Inclus
3 vidéos2 lectures2 devoirs
Afficher les informations sur le contenu du module
3 vidéos•Total 14 minutes
How Quality Monitoring Prevents Business Disasters•3 minutes
Building Quality KPI Monitoring Systems with Trend Analysis•6 minutes
Creating Quality KPI Dashboards with Trend Analysis•5 minutes
2 lectures•Total 20 minutes
Quality KPI Frameworks for Enterprise Data Systems•10 minutes
Advanced Remediation Strategies for Data Quality Issues•10 minutes
2 devoirs•Total 21 minutes
Quality KPI Analysis and Remediation Planning for Financial Services•18 minutes
Remediation Strategy Planning Review•3 minutes
Module 3: Integration & Assessment - Automated Error Handling Systems
Module 3•1 heure à terminer
Détails du module
Learners will create resilient automated SQL routines that detect, quarantine, and reprocess data errors without manual intervention, building self-healing data systems at enterprise scale.
Inclus
3 vidéos1 lecture2 devoirs1 laboratoire non noté
Afficher les informations sur le contenu du module
3 vidéos•Total 21 minutes
How Automated Error Handling Transforms Data Engineering Excellence•4 minutes
Automated Error Handling Architecture and SQL Implementation Patterns•11 minutes
Building Complete Automated Error Handling Systems in SQL•6 minutes
1 lecture•Total 10 minutes
Advanced SQL Patterns for Self-Healing Data Systems•10 minutes
2 devoirs•Total 15 minutes
Data Quality and Automated Error Handling Mastery Assessment•10 minutes
Automated SQL Error Handling and Recovery System•18 minutes
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