Data Integrity

Data Integrity is a critical concept in databases, systems design, and data management, focused on maintaining and ensuring the accuracy, consistency, and reliability of data over its entire life-cycle. Coursera's Data Integrity catalogue teaches you about the fundamental principles, methods, and techniques to enforce data integrity. You'll learn about various types of data integrity including entity, domain, referential, and user-defined, as well as the role of primary and foreign keys, constraints, and normalization in maintaining data integrity. Additionally, you'll gain insights into how data integrity can be compromised and effective strategies to prevent data corruption and loss. This skill is invaluable for roles such as database administrators, system designers, data scientists, and anyone involved in data management.
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Results for "data integrity"

  • Status: New

    Skills you'll gain: Looker (Software), Jupyter, Big Data, Business Analytics, Data Analysis, Data Visualization Software, Data Transformation, Google Sheets, Data Warehousing, SQL, Data Pipelines, Data Import/Export, Data Cleansing, Google Cloud Platform, Data Integrity

  • Skills you'll gain: Data Ethics, Responsible AI, Applied Machine Learning, MLOps (Machine Learning Operations), Machine Learning, Software Visualization, Data Integrity, Artificial Intelligence

  • Skills you'll gain: Responsible AI, Data Ethics, Service Design, Artificial Intelligence and Machine Learning (AI/ML), Data Integrity

  • Skills you'll gain: Responsible AI, Generative AI, Information Privacy, Google Cloud Platform, Secure Coding, Personally Identifiable Information, Information Systems Security, Data Security, Data Loss Prevention, Artificial Intelligence, Safety and Security, Data Integrity, Data Encryption Standard

  • Skills you'll gain: Responsible AI, Data Ethics, Artificial Intelligence, Interoperability, Testability, Data Integrity, Data Governance, Maintainability, Machine Learning

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