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    Amazon Dynamodb Data Modeling For Architects & Developers

    Posted By: ELK1nG
    Amazon Dynamodb Data Modeling For Architects & Developers

    Amazon Dynamodb Data Modeling For Architects & Developers
    Published 2/2023
    MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz
    Language: English | Size: 1.65 GB | Duration: 6h 4m

    Proven design patterns. best practices, tips on saving costs and more

    What you'll learn

    Use DynamoDB Data Modeling patterns

    Apply Best DynamoDB practices

    Leverage the right DynamoDb features in their applications

    Analyze use cases for DynamoDB

    Requirements

    NO programming experience

    Some experience with AWS Cloud

    Knowledge of any database

    A decent machine with internet connectivity

    An AWS account for some of the exercises

    Description

    Note:This course does NOT use AWS console for showing you basic DynamoDB operationsThis course does NOT focus on just coding This course primarily focusses on Data Modeling practices and patterns for Amazon DynamoDB. You will also learn DynamoDB best practices, tips and techniques for building modern and cost effective applications/microservices. At a high level, course is divided into 2 parts:Part-1            Objective: Build a solid understanding of DynamoDBHow DynamoDB works under the covers?Hands-on exercises to try out the DynamoDB API(s) using CLI and Python codeFeature/capability comparison with relational databasePart-2           Objective: Learn to apply DynamoDB design patternsLearn DynamoDB data modeling processHow to apply patterns to address business requirementsAnalyze the access patterns and identify the right pattern to useHands-on exercises to build a data model for a banking use case (refer:  ACME case study)Tools in useNoSQL workbenchLocal DynamoDB for model development & testingAWS cloud account for testing (minimal use)An integrated development environment (like Visual Studio Code)Python - if you would like to run the code samples on your machineGit clientIs this course for me?Yes - if you are an Architect responsible for designing apps on DynamoDBYes - if you are a Developer and aspiring to become an architectYes - if you are a DBA and looking to expand your skills to NoSQL databasesYes - if you are a Technologist who is curious on how DynamoDB works under the coversNo  - if you are just looking for basic how to tutorials on DynamoDBNo - if you are looking for coding DynamoDB appsCourse approachCourse does not assume that you already know DynamoDB. For that reasons, I am first covering the basics of DynamoDB. But unlike other courses, I will not just show you how-to use DynamoDB rather I will show you how DynamoDB works under the covers !! I strongly believe that to effectively use a database, an architect MUST understand how database technology works under the covers. Data modeling is an iterative process. I am sharing a prescriptive guidance on the process and then showing step-by-step how to apply the process. As a case study I am using an example of ACME bank (a fictitious retail bank). Throughout the course we will be applying the process to ACME bank use cases to evolve a full blown DynamoDB data model. Case study : ACME BankA fictitious bank that has embarked on a journey to modernize its retail banking systems. You are the Lead Architect for the retail banking modernization initiative. It is your responsibility:To  work with business owners to understand the requirementsTo model the data for DynamoDBProve/Disprove that DynamoDB will meet the application needsEducate stakeholders on DynamoDB capabilitiesHelp ACME Bank CTO to make a decision on whether to use DynamoDB or not

    Overview

    Section 1: Introduction

    Lecture 1 Introduction

    Lecture 2 Course outline & How to get the most out of this course

    Section 2: Tools, Local Development Environment

    Lecture 3 Setup Local DynamoDB and NoSQL Workbench

    Lecture 4 Exercise: NoSQL Workbench walkthrough

    Lecture 5 Exercise: Use CLI, Workbench with Local Table

    Lecture 6 Setup IDE and Git Repository

    Section 3: Amazon DynamoDB Fundamentals

    Lecture 7 DynamoDB: A Logical View

    Lecture 8 Table capacity fundamentals

    Lecture 9 Table capacity modes

    Lecture 10 Exercise: Try out the capacity modes

    Lecture 11 Item Attributes & Data Types

    Lecture 12 Exercise: Create a test model

    Lecture 13 DynamoDB Operations

    Lecture 14 Control Plane Operations

    Section 4: CRUD: Create API

    Lecture 15 Writes : Under the hood

    Lecture 16 API: PutItem, BatchWriteItem, Condition Expressions (7:14)

    Lecture 17 Exercise: Add Items to Student Table

    Section 5: CRUD: Retrieve API

    Lecture 18 Reads : Under the hood

    Lecture 19 API: GetItem, BatchGetItem, Scan

    Lecture 20 Queries : Under the hood

    Lecture 21 Queries & Key Condition Expression

    Section 6: CRUD: Update & Delete API

    Lecture 22 Update & Delete : Under the hood

    Lecture 23 API: UpdateItem

    Lecture 24 API: DeleteItem

    Section 7: CRUD : PartiQL Queries

    Lecture 25 CRUD : PartiQL Statements & API

    Section 8: DynamoDB Secondary Indexes

    Lecture 26 Indexes : Under the hood

    Lecture 27 Local Secondary Index (LSI)

    Lecture 28 Hands-On: Local Secondary Index

    Lecture 29 Global Secondary Index (GSI)

    Lecture 30 Hands-On: Global Secondary Index

    Section 9: Single Table Design

    Lecture 31 Single Table Vs. Multiple Table Design

    Lecture 32 Single table modeling process

    Section 10: Case Study : ACME Bank

    Lecture 33 ACME Bank Transformation Journey

    Lecture 34 ERD and Access patterns

    Section 11: Modeling : Entities

    Lecture 35 How to model an entity?

    Lecture 36 Hands-On: Design the Customer Entity

    Section 12: Modeling : Primary Keys

    Lecture 37 Patterns for primary key

    Lecture 38 Hands-On: Apply best practices for key

    Section 13: Modeling : One to Many Relationships

    Lecture 39 Patterns for one-to-many relationships

    Lecture 40 Analyze : Customer-Account Relationship

    Lecture 41 Hands-On: Embedding with Secondary Index

    Section 14: Modeling : Secondary Indexes

    Lecture 42 Hands-On: Add index for accessing customer on account

    Lecture 43 Hands-On: Model the transaction entity

    Lecture 44 Analysis : Taking advantage of sparse indexes

    Lecture 45 Hands-On: Add a sparse index for Customer-Txns

    Lecture 46 Analysis : Taking advantage of Index Overloading

    Lecture 47 Hands-On: Implement Overloaded GSI for Customer & Transaction

    Section 15: Modeling : Many-to-Many Relationship

    Lecture 48 Adjacency List Pattern

    Lecture 49 Analysis : Customer-Offer Relationship

    Lecture 50 Hands-On: Apply adjacency pattern to customer-offer relationship

    Section 16: Modeling : Preventing Hot Partitions

    Lecture 51 Hot Partitions & Sharding patterns

    Lecture 52 Hands-On : Address hot partition issue

    Section 17: Modeling : Efficient Scans

    Lecture 53 Hands-On: Experimenting with parallel scan

    Lecture 54 Analysis : Scan Vs. GSI for for txns in date range

    Section 18: ACID Transactions

    Lecture 55 What are ACID Transactions?

    Lecture 56 API: TransactWriteItems

    Lecture 57 Hands-On: TransactWriteItems API

    Lecture 58 TransactWriteItems Idempotence

    Lecture 59 API : TransactGetItems

    Section 19: Modeling : Transactions

    Lecture 60 Hands-On : Running counters

    Lecture 61 Hands-On : Credit Transactions

    Lecture 62 Hands-On: Debit Transaction

    Section 20: DynamoDB Streams

    Lecture 63 DynamoDB Streams

    Lecture 64 Shards & Stream Reader Application

    Lecture 65 Hands-On: Experiment with Streams API

    Lecture 66 Hands-On: Tryout API with Python

    Section 21: Modeling : DynamoDB Streams

    Lecture 67 Modeling : Setup daily report

    Solution Architects,Cloud application Developers,Cloud Engineers,Database Administrator interested in learning NoSQL databases