
Explore Collibra data quality essentials, from adaptive rules and nine dimensions to custom rule creation, scheduling, alerts, and hands-on labs with healthcare and pharma case studies.
Explore Collibra's data quality benefits: auto generated rules, machine learning driven adaptive data quality, scalable profiling, data reconciliation, sensitivity labeling, and self-service scoring with personalized alerts to boost enterprise trust.
Modify adaptive data quality rules in Collibra to automate validation and profile data as it grows, building a behavior model. Learn to view, profile, and adjust adaptive thresholds and ranges.
Explore how adaptive rules in Collibra perform data quality checks on healthcare data, monitoring rows, execution time, distribution, completeness, conformity, and outliers, with adjustable bounds.
Discover how to create and apply custom data quality rules in Colibra using the rule builder, SQL checks, and dataset search, so a data quality job runs the rules.
Explore data quality scoring across nine dimensions in Collibra's data quality dashboard to preserve data integrity. Learn how behavior and custom rules, built with sql, automate quality checks on datasets.
Colibra's data quality scoring identifies and reports outliers using machine learning and analyzes patterns to detect values that break locality and zip code patterns.
Master Data Quality with Ease
Learn Data Quality (DQ) Collibra functionality quickly with a simple, beginner-friendly approach. No overwhelming jargon or complex concepts—just clear, practical insights to help you get started with confidence.
Learn what you can expect from a modern Data Quality tool quickly!
Data Quality & Observability is considered by many the best way to manage your data sets by learning through observation rather than human input. It applies the latest advancements in Data Science and Machine Learning to the problem of Data Quality—surfacing data issues in minutes instead of months.
This is a course for absolute beginners who have never used a Data Quality & Observability platform. We will cover the main features without going into too much detail so you can quickly become familiar with the tool and its capabilities.
Why This Course?
Simplicity First: Designed for beginners, this course breaks down DQ functionality into easy-to-understand steps.
Real-World Applications: Learn how to apply DQ tools in practical scenarios to enhance data governance and reliability.
Hands-On Learning: Gain direct experience with workflows, profiling, and rules creation to ensure data accuracy.
What You Will Learn:
Introduction to Data Quality Features:
Overview of key Data Quality capabilities.
How Data Quality integrates into broader data governance frameworks.
Core Data Quality Features:
Setting up and managing Data Quality Rules.
Automating data profiling and anomaly detection.
Using workflows for cleansing and monitoring.
Key Data Quality Concepts:
Data profiling and its role in understanding datasets.
Data standardization and cleansing.
Record linkage and identity resolution for accurate entity management.
Adaptive Rules with Hands-On Lab:
Creating custom DQ rules.
Scheduling DQ jobs and alerts.
Exploring 9 dimensions of Data Quality with examples.
Understanding Views in Data Quality tools.
Performing hands-on labs and working through a case study example.
Running Data Quality Checks (DQ Checks).
Reviewing and analyzing reports, scorecards, and managing rules and alerts.
Best Practices:
Aligning DQ rules with organizational standards.
Using dashboards for continuous monitoring and reporting.
Integrating DQ checks with existing data pipelines for seamless governance.
Course Benefits:
Clear, beginner-friendly explanations of Data Quality concepts.
Step-by-step tutorials to build confidence in using DQ tools.
Practical examples and workflows to solidify your understanding.
Who This Course Is For:
Data Management Beginners: Start your Data Quality journey.
Data Governance Professionals: Enhance your skills in Data Quality.
Business Analysts & Managers: Understand how DQ ensures data reliability.
Unlock the power of Data Quality and transform your approach to managing data!
Let me know if you'd like this rewritten with a different tool’s name or tailored to a specific platform like Ataccama or Informatica.
Learn Data Quality (DQ) functionality quickly with a simple, beginner-friendly approach. No overwhelming jargon or complex concepts—just clear, practical insights to help you get started with confidence.
Learn what you can expect from a modern Data Quality tool like Collibra—fast!
Collibra Data Quality & Observability is considered one of the best platforms to manage your datasets by learning through observation rather than relying solely on human input. It applies the latest advancements in Data Science and Machine Learning to detect and surface data issues in minutes instead of months.
This course is for absolute beginners who have never used a Data Quality & Observability platform like Collibra. We will cover the main features without going into too much technical depth so you can quickly become familiar with the tool and its capabilities.