Understanding Modern Data Architecture
| Course Details | ||||||||
|---|---|---|---|---|---|---|---|---|
|
||||||||
| Languages | ||||||||
|
||||||||
| Outcomes | ||||||||
|
||||||||
| Price & Terms | ||||||||
|
||||||||
| Technical | ||||||||
|
||||||||
| Specification | ||||||||
|
||||||||
Compare modern data architectures, learn their storage, processing, governance and security layers, and design a data platform for a business case.
Every day organizations have more data to process, and a data platform has to be designed to store, move and serve it. Here, modern data architecture is treated as a set of layers plus shared services: storage, ingestion, processing and serving on one side, with governance, metadata, security and observability running across all of them. Along the way you weigh designs such as Lambda, Kappa, Data Mesh and Data Fabric against traditional approaches.
What You Will Achieve
- Tell Lambda, Kappa, Data Mesh and Data Fabric designs apart and say which use case each one suits
- Choose between blob storage, SQL and NoSQL stores, and batch or streaming processing for a given need
- Describe data governance roles and classify data security measures when planning a platform
- Gather business requirements and design an architecture that meets them while keeping storage and processing costs in view
Program Overview
Architecture Types and Core Layers
Compares well-known architecture designs with traditional ones, then walks through the layers that store, ingest, process and serve data.
- Modern vs. traditional architectures
- Lambda, Kappa, Data Mesh and Data Fabric
- Storage types, ingestion and the landing zone
- Batch and streaming processing, and serving technologies
Governance, Security and Orchestration
Covers the shared services that run across every layer and keep a platform governed, secure, observable and affordable in the cloud.
- Data governance roles and metadata types
- Data security and virtual private clouds
- Observability and troubleshooting
- Orchestration, sensors, storage classes and reserved capacity
Designing and Evaluating a Data Platform
Brings the earlier parts together in a business case where you gather requirements, then design and judge a data platform.
- Asking the right questions
- Ingesting application data
- The purpose of a quarantine zone
- Evaluating architecture solutions
Certificate Awarded (Paid)
Job Outlook
These skills apply wherever teams plan and run data platforms: deciding how data is stored, ingested and served, setting governance and security rules, and keeping cloud storage and processing costs under control.
Good for: Data engineers, architects and technical managers who plan or review data platforms and want a clear way to compare architecture options.
Keep in mind: It stays at the level of concepts: no coding is required, and the course centers on architectural choices rather than hands-on building.
Bottom line: A compact look at how platform layers and cross-cutting services fit together, closed by a business case that asks you to design one.
Frequently Asked Questions
Which data architectures are compared in the lessons?
The first chapter sets modern designs against traditional ones and looks at Lambda architecture and its layers, Kappa architecture and what happens to the batch layer there, and the Data Mesh and Data Fabric approaches, ending with how each relates to use cases.
What does the closing business case involve?
You work through a design exercise: asking the right questions about the business requirements, planning how the application data is ingested, considering why a quarantine zone is useful, and then designing and evaluating a modern data platform that fits the case.
How are cloud costs handled in the lessons?
Cost appears alongside orchestration in the final chapter, which covers best practices for storage and processing costs, reserved capacity in cloud services, and the use of storage classes to keep spending on a data platform under control.
Is Apache Airflow used in the course?
Orchestration is taught as a concept, including how it differs from scheduling and what orchestration sensors do. The final chapter names tools such as Apache Airflow, but the course focuses on architectural concepts rather than hands-on coding.
User Reviews
Write your review
You must be logged in to post a review.
Reviews can only be posted by registered learners. Log in or create a free account, then you will return here to post.
There are no reviews yet.