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所在平台: Udemy |
课程主页: https://www.udemy.com/course/data-vault-mastery/
课程评论：没有评论
## Data Vault 精通：现代化数据仓库，助力高级分析 本课程为期深入的综合培训，旨在帮助学员掌握利用数据仓库方法论在现代数据仓库环境中发挥数据仓库优势的技能和知识。课程重点关注最新的数据仓库 2.0 进展，为学习者在建模、实施和管理技术方面打下坚实基础，以支持高级分析。此外，还将探讨主数据管理（MDM）、元数据管理、多维数据库和数据仓库平台等其他数据相关方面。 **核心学习目标：** * **理解基础：** 掌握数据仓库、数据仓库方法论的核心概念，以及在高级分析时代进行现代化的必要性。 * **掌握数据仓库 2.0 架构：** 探索数据仓库 2.0 架构，理解其如何实现大规模、灵活和适应性强的动态数据环境。 * **学习数据仓库建模：** 深入学习数据仓库 2.0 建模技术，包括设计 Hub、Link 和 Satellite 以捕获历史数据和管理变更。 * **实施数据仓库加载模式：** 获得实施数据仓库 2.0 加载模式的实践经验，高效地将各种来源的数据加载到数据仓库中。 * **理解数据仓库物理 ETL 加载：** 了解用于填充数据仓库的数据仓库提取、转换、加载（ETL）过程的物理实现。 * **认识数据仓库 2.0 哈希键：** 学习数据仓库 2.0 中哈希键在提升数据性能和管理数据完整性方面的重要性。 * **发现维度建模：** 介绍维度建模技术，包括星型模式和多星型模式，以支持报告和分析。 * **精通主数据管理：** 涵盖主数据管理的架构和开发步骤，以确保组织内主数据的一致性和准确性。 * **揭示元数据管理：** 探索不同的元数据类型，理解如何捕获和管理元数据以实现有效的数据治理。 * **深入多维数据库：** 深入了解多维数据库的世界，以及它们如何满足复杂的分析查询需求。 * **探索数据仓库平台：** 考察数据仓库 2.0、IBM 数据与分析产品以及 AWS 数据与分析服务的技术图景。 完成本课程后，学员将能够设计、实施和管理强大的数据仓库结构，以支持高级分析，并从数据资产中获得有价值的见解。
Course Overview:Data Vault Mastery: Modernizing Data Warehousing for Advanced Analytics is an in-depth and comprehensive training program designed to equip participants with the skills and knowledge required to leverage the power of data vault methodologies in modern data warehousing environments. This course focuses on the latest advancements in data vault 2.0, providing learners with a solid foundation in data modeling, implementation, and management techniques for supporting advanced analytics.You also have a chance to open knowledge on other data aspects such as: Master Data Management (MDM), Metadata Management, Multidimensional Databases and Data Warehouse Platform, etcCourse Objectives:Understand the Fundamentals: Participants will grasp the core concepts of data warehousing, data vault methodologies, and the need for modernization in the era of advanced analytics.Master Data Vault 2.0 Architecture: Learners will explore the architecture of Data Vault 2.0 and understand how it addresses scalability, flexibility, and adaptability for handling dynamic data environments.Learn Data Vault Modeling: The course delves into Data Vault 2.0 modeling techniques, covering the design of hubs, links, and satellites to capture historical data and manage changes.Implement Data Vault Load Patterns: Participants will gain hands-on experience in implementing Data Vault 2.0 load patterns for efficiently loading data from various sources into the data warehouse.Explore Data Vault Physical ETL Load: The course provides insights into the physical implementation of ETL (Extract, Transform, Load) processes for populating the Data Vault.Understand Data Vault 2.0 Hash Key: Learners will learn about the significance of hash keys in Data Vault 2.0 for enhancing data performance and managing data integrity.Discover Dimensional Modeling: Participants will be introduced to dimensional modeling techniques, including star schemas and multi-star schemas, to support reporting and analytics.Master Data Management: The course covers the architecture and development steps of Master Data Management (MDM) to ensure consistent and accurate master data across the organization.Unveil Metadata Management: Learners will explore different metadata types and understand how to capture and manage metadata for effective data governance.Dive into Multidimensional Databases: Participants will gain insights into the world of multidimensional databases and how they cater to complex analytical queries.Explore Data Warehouse Platforms: The course examines the technology landscape of Data Vault 2.0, IBM's Data & Analytics products, and AWS Data & Analytics servicesBy the end of the "Data Vault Mastery: Modernizing Data Warehousing for Advanced Analytics" course, participants will be well-equipped to design, implement, and manage robust data vault structures to support advanced analytics and derive valuable insights from their data assets.
