What you’ll learn
- Learning What Data Architecture 2.0 is and why it’s relevant
- Analyzing an overview of types, layers, frameworks, and DBMSs of data architecture
- Understanding Data Architecture 2.0: Functions, Principles, and Patterns
- Analyze the Data Architecture of Business and Business Intelligence
- Observing an overview of the career path and skills you’ll need to become a data architect
This course includes:
- 1 hour on-demand video
- Access on mobile and TV
- Full lifetime access
- Certificate of completion
Fundamental Course of Data Architecture 2.0 (101 level)
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 Fundamental Course of Data Architecture 2.0 (101 level):
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
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