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Microsoft Azure Cosmos DB Developer Specialty (DP-420) Cert Prep: 1 Design and Implement Data Models by Microsoft Press

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Cosmos DB is Microsoft Azure's flagship non-relational database product. It supports multiple application programming interfaces (APIs) that provide compatibility with competing NoSQL databases. If you’re looking to integrate enterprise-scale, cloud-based, NoSQL databases into your organization’s IT solutions, you may want to think about getting certified as a Microsoft Azure Cosmos DB developer. In this course, the first in a five-part series, instructor Tim Warner gives an overview of the skills you need to master to tackle the first domain of the Microsoft Azure Cosmos DB Developer Specialty (DP-420) certification exam. Learn how to design and implement a non-relational data model for Azure Cosmos DB, design a data-partitioning strategy for Azure Cosmos DB Core API, plan and implement sizing and scaling for a database created with Azure Cosmos DB, implement client connectivity options in the Azure Cosmos DB SDK, and implement data access using the Azure Cosmos DB SQL query language and SQL API SDKs.

Note: This course was created by Microsoft Press and Tim Warner. We are pleased to host this training in our library.


1 Introduction
  • 01 Exam DP-420 Designing and implementing cloud-native applications using Microsoft Azure Cosmos DB Introduction

  • 2 Lesson 1
  • 02 Learning objectives
  • 03 Develop a design by storing multiple entity types in the same container
  • 04 Develop a design by storing multiple related entities in the same document
  • 05 Develop a design by referencing between documents
  • 06 Identify primary and unique keys
  • 07 Identify data and associated access patterns
  • 08 Specify a default TTL on a container for a transactional store

  • 3 Lesson 2
  • 09 Learning objectives
  • 10 Choose a partition strategy based on a specific workload
  • 11 Plan for transactions when choosing a partition key
  • 12 Calculate and evaluate throughput distribution based on partition key selection
  • 13 Design partitioning for workloads that require multiple partition keys

  • 4 Lesson 3
  • 14 Learning objectives
  • 15 Choose between serverless and provisioned models
  • 16 Choose when to use database-level provisioned throughput
  • 17 Design for granular scale units and resource governance
  • 18 Evaluate the cost of the global distribution of data
  • 19 Configure throughput for Azure Cosmos DB by using Azure Portal

  • 5 Lesson 4
  • 20 Learning objectives
  • 21 Implement a connectivity mode
  • 22 Create a connection to a database
  • 23 Enable offline development by using the Azure Cosmos DB Emulator
  • 24 Handle connection errors
  • 25 Configure client-side threading and parallelism options
  • 26 Enable SDK logging

  • 6 Lesson 5
  • 27 Learning objectives
  • 28 Implement queries that use arrays, nested objects, aggregation, and ordering
  • 29 Implement a correlated subquery
  • 30 Implement queries that use array and type-checking functions
  • 31 Implement queries that use mathematical, string, and date functions
  • 32 Implement queries based on variable data

  • 7 Lesson 6
  • 33 Learning objectives
  • 34 Choose when to use a point operation versus a query operation
  • 35 Implement a point operation that creates, updates, and deletes documents
  • 36 Implement an update by using a patch operation
  • 37 Manage multi-document transactions using SDK Transactional Batch
  • 38 Perform a multi-document load using SDK Bulk
  • 39 Implement optimistic concurrency control using ETags
  • 40 Implement session consistency by using session tokens
  • 41 Implement a query operation that includes pagination
  • 42 Implement a query operation by using a continuation token
  • 43 Handle transient errors and 429s
  • 44 Specify TTL for a document
  • 45 Retrieve and use query metrics

  • 8 Lesson 7
  • 46 Learning objectives
  • 47 Design stored procedures to work with multiple items transactionally
  • 48 Implement triggers
  • 49 Implement a user-defined function
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