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Data Standardization Frameworks
Published 1/2024 MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz Language: English | Size: 77.04 MB | Duration: 0h 32m Data Standardization Mastery: Consistency, Collaboration. Format Consistency, Industry-Specific Standards What you'll learn Understanding of Data Standardization Concepts: Learners will gain a solid understanding of the concept of data standardization Key Aspects of Data Standardization: You will be familiar with the key aspects of data standardization, such as format consistency Benefits of Data Standardization: Understand the wide-ranging benefits of data standardization, including improved data quality, enhanced data integration Types of Data Standardization: Various types of data standardization, such as format standardization, categorical standardization, unit standardization etc Data Standardization Frameworks: such as ISO/IEC 11179, Data Documentation Initiative (DDI), HL7, ISO 20022, OGC Standards, W3C Standards, GS1 Standards Data Standardization in Industry Verticals: explore how data standardization is applied in various industry verticals, including healthcare, finance, retail etc Data Standardization Best Practices: gain insights into best practices for data standardization, including considerations for format consistency etc Requirements Some Knowledge of Data Analysis Description Overview Section 1: Introduction Lecture 1 Introduction to the Data Standardization Course Lecture 2 Impact of Data Standardization Lecture 3 Aspects of Data Standardization Section 2: Data Standardization Frameworks Lecture 4 Frameworks of Data Standardization Lecture 5 Data Wrangling Lecture 6 Data Standardization Lecture 7 Data Orchestration Lecture 8 Data Blending Lecture 9 Data Cleaning Lecture 10 Data Transformation Lecture 11 Data Integration and Data Enrichment Section 3: Conclusion Lecture 12 Bonus Lecture Data Analysts: Professionals responsible for analyzing and interpreting complex datasets to inform business decisions.,Data Scientists: Individuals who apply advanced statistical and mathematical techniques to extract insights and build predictive models from data.,Database Administrators (DBAs): Professionals responsible for the installation, configuration, and maintenance of database management systems.,Data Quality Analysts: Individuals ensuring the accuracy, completeness, and consistency of data through various quality assurance processes.,Business Intelligence (BI) Developers: Professionals building tools and systems for gathering, storing, and analyzing business data to support decision-making.,Data Governance Professionals: Individuals responsible for establishing and enforcing data management policies and practices within an organization.,Data Stewards: Professionals who ensure that data assets are properly managed, protected, and used in compliance with organizational policies.,Business Analysts: Professionals bridging the gap between business needs and data solutions, translating requirements into actionable insights.,Students and Aspiring Data Professionals: Individuals pursuing a career in data science, analytics, or related fields who can benefit from a foundational understanding of data standardization.