Architecting Big Data Applications: Batch Mode Application Engineering

Course Overview

Learn about use cases and best practices for architecting batch mode applications using big data technologies such as Hive and Apache Spark.

Course Circullum

Introduction

Welcome
Platforms vs. applications
Software architecture vs. design
Notes on use cases

1. Intro to Big Data Applications

Big data characteristics
Traditional vs. big data applications
Big data application modules
Technologies for big data
Strategy for big data apps

2. Use Case 1: Data Warehouse (DW)

DW: Analyze the problem
DW: Outline the solution
DW: Consider technologies
DW: Lay out the architecture
DW: Design key elements
Best practices: Data acquisition

3. Use Case 2: Log Accumulation (LA)

LA: Analyze the problem
LA: Outline the solution
LA: Consider technologies
LA: Lay out the architecture
LA: Design key elements
Best practices: Data transport

4. Use Case 3: IT Operations Analytics (OA)

OA: Analyze the problem
OA: Outline the solution
OA: Consider technologies
OA: Lay out the architecture
OA: Design key elements
Best practices: Data processing

5. Use Case 4: Customer 360 (C360)

C360: Analyze the problem
C360: Outline the solution
C360: Consider technologies
C360: Lay out the architecture
C360: Design key elements
Best practices: Data storage

6. Use Case 5: Customer Analytics (CA)

CA: Analyze the problem
CA: Outline the solution
CA: Consider technologies
CA: Lay out the architecture
CA: Design key elements
Best practices: Data service

Conclusion

Next steps

Kumaran Ponnambalam

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