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UNIT CONTENTS
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  Previous Unit: Data Model Anti-Patterns
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DSE Version: 6.0

Data Modeling Use Cases

Video

Exercises

In this unit, we will be looking at some use cases and creating some data models for them, to exercise our knowledge of Apache Cassandra data modeling techniques.

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Exercise 6.1: Use Case 1 - Shopping Cart

You are an application developer for Widgets International, a company that manufactures widgets and sells them exclusively via their online storefront. Your company has made the decision to migrate its online storefront to a DSE based application. Analyze the conceptual design and application workflow fragment for this exercise and write the CQL to implement the shopping cart and the product catalog.

Conceptual Design



Application Workflow

Exercise 6.2: Use Case 2 - Customer Profile

Widgets International loves the shopping cart design for the online storefront scenario presented in the previous exercise and has brought you some new requirements. In conversations with the business, you learn that it will be important to store multiple phone numbers, addresses and email addresses for each customer. This data will be read/write intensive and it is important to keep latency to 50ms or less. Also, since passwords will be stored, encryption is mission-critical. Analyze the same conceptual design and application workflow from the previous exercise and write the CQL to implement these customer profile requirements.

Exercise 6.3: Use Case 3 - Sensor Event Tracking

Widgets International is so pleased with the work that you have done in the previous two exercises that they are tasking you to solve a new problem related to their manufacturing facilities.

The widgets made by your company are sensitive, high tech devices, and each machine used in the manufacturing process contains one or more sensors that captures data such as temperature, speed of a moving part, etc. This data is now going to be stored in a DSE cluster that you must design and maintain. Once the application is up and running, the data it captures will be provided to analytics tool chains.

The application will definitely be write heavy; tens of millions of events will be generated per second, and your company has an SLA requiring that all events be persisted across multiple nodes in your DSE cluster in less than 10ms.

Analyze the conceptual design below and write the CQL to implement the table(s) needed to store this data.

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