The Master Course in Data Architecture 2.0 is a comprehensive program that provides learners with the knowledge and skills necessary to design and implement data architectures for modern data-driven applications. The course covers a range of topics, including data modeling, data integration, data warehousing, and data governance. Learners will also gain an understanding of the latest trends and best practices in data architecture, including big data technologies and cloud-based architectures.
Through hands-on exercises and projects, learners will gain practical experience working with data architecture tools and techniques, and will learn how to design scalable and resilient data architectures that can support the needs of modern applications.
This course is ideal for data architects, database administrators, and IT professionals who want to deepen their understanding of data architecture and stay up-to-date with the latest trends and technologies in the field.
Description Master course in Data Architecture 2.0
How Do I Understand Data Architecture?
Data architecture is a set of rules, policies, standards, and models that determine what type of data is collected, how it’s used, stored, managed and integrated within an organization and its database systems. An organization’s IT systems and applications are able to create and manage data flows and how they are processed.
There are a lot of processes and methodologies that address data at rest, data in motion, data sets, and how they relate to data-dependent processes and applications. An organization’s data sourcing and management strategy should include the primary data entities, types, and sources. A data architect usually designs, creates, deploys and manages data architecture.
Data architecture is imperative for many reasons, including: Helps you better understand your data. Describes how to manage data from initial capture to information consumption. Develops and implements a structured data management system.
Three layers make up enterprise data architecture:
· Data conceptual/business model: Includes all data entities and provides a semantic model
· Data logical/system model: Describes how data entities are linked up
· The physical/technology model is how a specific process and functionality are implemented on the underlying technology infrastructure.
There are 5 main topics I’d like to teach in this master’s course:
1. What Data Architecture 2.0 is and why it’s relevant
2. An overview of types, layers, frameworks, and DBMSs
3. Data Architecture 2.0: Functions, Principles, and Patterns
4. The Data Architecture of Business and Business Intelligence
5. An overview of the career path and skills you’ll need to become a data architect