# Data Analytics Course Strawman
TODO - This example page is being updated for 14Nov launch.
UniSA is developing a data analytics course and is seeking support from AWS for hands on labs to augment the lectures and tutorials for weeks 1 thru 4
UniSA POC -
AWS POC -

## Scope
from

Program Objectives
- Develop, apply, and demonstrate an understanding of the fundamentals of data analytics for business aligned to A) AWS Cloud practitioner LINK / OR B) Data Analyst Practitioner D2D CRC / SFIA level 3/4*
- Apply discipline knowledge to solve a real-world client problem;
- Use global professional skills as part of a virtual consulting project team

## Out of Scope
Custom AWS training
NOTE: AWS Educate or AWS Academy resources may also be suitable

## References

# Course Strawman
This section includes hands on labs, additional reading and related reference materials for students from AWS. TODO validate this section with UniSA via a table top walkthrough from the perspective of lecturers and students.

This section is comprised of publically available links and information.

## Wk1 - Cloud Computing Essentials
Content
- What is cloud computing?
- Around the world with AWS
- AWS Services from 20,000 feet
- The Console
- The command line (CLI)
- The SDK
- IAM

### Wk1 lab https://aws.amazon.com/getting-started/hands-on/host-static-website/

### Hands on Labs
- Title: AWS Modern Data Architecture Immersion Day
- Duration: Reduce from a full day to perhaps 2 hours. (6 hours total)
- Link: https://tinyurl.com/4me2d278
- Short Description:
This hands on workshop introduces students to modern data architecture, which focuses on leveraging the flexibility and elasticity of cloud computing to reduce the 'time to inights' for data professionals.
- Prerequisites: None
- Delivery Format: Virtual or In the lab. Can be both if needed.
- Objectives:
Students are introduced to:
- Scalable Data Lakes
- Purpose Built Data Services
- Seamless Data Movement
- Unified Governance
- Performant and Cost Effective

### Self Paced Labs
- Title: Data Analytics Fundamentals
- Subtitle: Lesson 1: Introduction to data analysis solutions
- Duration: Lesson 1 only (TODO timing)
- Link: https://tinyurl.com/3dmnxxhh
- Delivery Format: Digital Training
- Objectives:
- Data analytics and data analysis concepts
- Introduction to the challenges of data analytics

### Further Reading
This section provides a range of reading, use cases, detailed documentation and coded solutions. Students may find some or all of these links interesting in terms of the 'art of the possible' and for deep diving into the technical minutiae of applied data analytics. These links provide a view into the data analyst at work.

#### Case Studies and Blog Posts
- Case Study = Wynk Slashes Compute Costs for Big Data by 60% with Amazon EMR and Spot Instances https://aws.amazon.com/solutions/case-studies/wynkmusic/
- AWS Blog Post - AWS serverless data analytics pipeline reference architecture https://aws.amazon.com/blogs/big-data/aws-serverless-data-analytics-pipeline-reference-architecture/

#### Reference Architectures and Coded Solutions
- Modern Data Analytics Reference Architecture on AWS https://d1.awsstatic.com/architecture-diagrams/ArchitectureDiagrams/modern-data-analytics-using-lake-house-ra.pdf?anld_da6
- Harness the power of your data with AWS Analytics https://aws.amazon.com/blogs/big-data/harness-the-power-of-your-data-with-aws-analytics/ This blog post introduces modern analytics designs that scale massively

#### Documentation
- Where can you start reading about the myriad of AWS analytics services, use cases and reference material? https://aws.amazon.com/big-data/datalakes-and-analytics/

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TODO more to follow

## Wk2 - Storage and Compute

### Hands on Labs
Title:
Duration:
Link:
Short Description:
Prerequisites:
Delivery Format:

### Self Paced Labs
Title:
Duration:
Link:
Short Description:
Prerequisites:
Delivery Format:

### Further Reading

#### Case Studies and Blog Posts

#### Documentation

## Wk3 - Database in Practice

### Hands on Labs
Title:
Duration:
Link:
Short Description:
Prerequisites:
Delivery Format:

### Self Paced Labs
Title:
Duration:
Link:
Short Description:
Prerequisites:
Delivery Format:

### Further Reading

#### Case Studies and Blog Posts

#### Documentation

## Wk4 - Networking Concepts

### Hands on Labs
Title:
Duration:
Link:
Short Description:
Prerequisites:
Delivery Format:

### Self Paced Labs
Title:
Duration:
Link:
Short Description:
Prerequisites:
Delivery Format:

### Further Reading

#### Case Studies and Blog Posts

#### Documentation

# AWS Digital Training
## Data Analytics Fundamentals
Title: Data Analytics Fundamentals
Duration: 3h 30m
Link:
Short Description:
In this self-paced course, you learn about the process for planning data analysis solutions and the various data analytic processes that are involved. This course takes you through five key factors that indicate the need for specific AWS services in collecting, processing, analyzing, and presenting your data. This includes learning basic architectures, value propositions, and potential use cases. The course introduces you to the AWS services and solutions to help you build and enhance data analysis solutions.

Prerequisites:
- Working knowledge of database concepts
- Basic understanding of data storage, processing, and analytics
- Experience with enterprise IT systems

Delivery Format: Digital Training

#### Course Outline

This course covers the following concepts:

• Lesson 1: Introduction to data analysis solutions

- Data analytics and data analysis concepts

- Introduction to the challenges of data analytics

• Lesson 2: Volume – data storage

- Introduction to Amazon S3

- Introduction to data lakes

- Introduction to data storage methods

• Lesson 3: Velocity – data processing

- Introduction to data processing methods

- Introduction to batch data processing

- Introduction to stream data processing

• Lesson 4: Variety – data structure and types

- Introduction to source data storage

- Introduction to structured data stores

- Introduction to semistructured and unstructured data stores

• Lesson 5: Veracity – cleansing and transformation

- Understanding data integrity

- Understanding database consistency

- Introduction to the ETL process

• Lesson 6: Value – reporting and business intelligence

- Introduction to analyzing data

- Introduction to visualizing data

• Lesson 7: Key Takeaways

- Putting the pieces together

- What’s next#