Tutorials > Data Engineering on AWS Vol 1 OLAP & Data Warehouse
Data Engineering on AWS Vol 1 OLAP & Data WarehouseDate: 30 June 2026 | Posted by: AD-TEAM |
![]() Data Engineering On Aws Vol 1 - Olap & Data Warehouse MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz Language: English | Size: 18.7 GB | Duration: 46h 26m Detailed training (Level 350) on AWS Data Engineering Services Redshift, S3, Athena, Hive, Glue Catalog, Lakeformation What you'll learn Understand Data Engineering (Volume 1) on AWS using S3, Redshift, Athena and Hive Know Redshift, S3 and Athena up to Level 350+ with HANDS-ON Production level projects and hands-on to help candidates provide on-job-like training Get access to datasets of size 100 GB - 200 GB and practice using the same Learn Python for Data Engineering with HANDS-ON (Functions, Arguments, OOP (class, object, self), Modules, Packages, Multithreading, file handling etc. Learn SQL for Data Engineering with HANDS-ON (Database objects, CASE, Window Functions, CTE, CTAS, MERGE, Materialized View etc.) Requirements Good to have AWS and SQL knowledge Description This is Volume 1 of Data Engineering course on AWS. This course will give you detailed explanations on AWS Data Engineering Services like S3 (Simple Storage Service), Redshift, Athena, Hive, Glue Data Catalog, Lake Formation. This course delves into the data warehouse or consumption and storage layer of Data Engineering pipeline. In Volume 2, I will showcase Data Processing (Batch and Streaming) Services. You will get opportunities to do hands-on using large datasets (100 GB - 300 GB or more of data). Moreover, this course will provide you hands-on exercises that match with real-time scenarios like Redshift query performance tuning, streaming ingestion, Window functions, ACID transactions, COPY command, Distributed & Sort key, WLM, Row level and column level security, Athena partitioning, Athena WLM etc. Some other highlights:Contains training of data modelling - Normalization & ER Diagram for OLTP systems. Dimensional modelling for OLAP/DWH systems.Data modelling hands-on.Other technologies covered - EC2, EBS, VPC and IAM.This is Part 1 (Volume 1) of the full data engineering course. In Part 2 (Volume 2), I will be covering the following Topics.Spark (Batch and Stream processing using AWS EMR, AWS Glue ETL, GCP Dataproc)Kafka (on AWS & GCP)FlinkApache AirflowApache PinotAWS Kinesis and more. Overview Section 1: Introduction - Data Engineering Volume 1 on AWS Lecture 1 Course Introduction and Resources Lecture 2 2. Course Introduction and Course Contents Lecture 3 Course Details - Projects, About Me Section 2: (Optional) AWS Pre-requisites - EC2 & EBS Lecture 4 AWS Cloud and EC2 Introduction Lecture 5 EC2 Console & HandsOn Lecture 6 EBS Theory Lecture 7 EBS Hands On Section 3: (Optional) AWS Pre-requisites - VPC Lecture 8 VPC Introduction & Components Lecture 9 VPC Components Hands On Lecture 10 Bastion Host Lecture 11 Security Groups Lecture 12 NAT Gateway & VPC Endpoint Lecture 13 VPC Peering Section 4: (Optional) AWS Pre-requisites - IAM Lecture 14 IAM Introduction & Hands On Lecture 15 IAM Service Roles Section 5: (Optional) Non AWS Pre-requisites - SQL Basics Lecture 16 1. SQL Introduction Lecture 17 2. SQL Client & Server Setup Lecture 18 3. SQL Database Objects Theory Lecture 19 4. Database Objects Hands On Lecture 20 5. CRUD Operations Lecture 21 6. SELECT Operators Lecture 22 7. CASE COALESCE Functions Lecture 23 8. DATE Functions Lecture 24 9. CTAS Cast Concat Lecture 25 10. Update Delete Truncate Lecture 26 11. HAVING Clause Lecture 27 12. Inner Join, Left Join, Right Join, Outer Join Lecture 28 13. Union Intersect View Lecture 29 14. Materialized View Lecture 30 15. Common Table Expression (CTE) Lecture 31 16. SQL Window Functions Lecture 32 17. MERGE statement & Summary Section 6: (Optional) Non AWS Pre-requisites - Python Basics Lecture 33 1. Python Intro - Architecture, PyCharm, Virtual Env Lecture 34 2. PyCharm & CLI Walkthrough Lecture 35 3. Compiled vs Interpreted Lecture 36 4. Everything is Python is Object Lecture 37 5. String Data Type Lecture 38 6. Number Data Type Lecture 39 7. List Data Type Lecture 40 8. Tuple Data Type Lecture 41 9. Set & Dict Data Type, Type Conversion Lecture 42 10. Python Operators Lecture 43 11. Set up Python interpreter in PyCharm Lecture 44 12. Print & Input Functions Lecture 45 13. IF Statement Lecture 46 14. For & While loops Lecture 47 15. Functions Intro Lecture 48 16. Function Scoping Lecture 49 17. Functions RETURN Lecture 50 18. Function Arguments Lecture 51 19. Modify Arguments Lecture 52 20. Positional & Keyword Arguments Lecture 53 21. args & kwargs Lecture 54 22. Class Object Self Lecture 55 23. Class-Instance Variables, __init__ Lecture 56 24. Class Object Exercise 1 Lecture 57 25. Class Object Exercise 2 Lecture 58 26. Inheritance Lecture 59 27. Python Memory Management Lecture 60 28. Modules & Packages Lecture 61 29. HandsOn Exercise Lecture 62 30. Module Pre-compilation Lecture 63 31. Namespace & __name__ Lecture 64 32. Error Handling in Python Lecture 65 33. File Handling Lecture 66 34. CSV & JSON module Lecture 67 35. Python Multi-threading concept Lecture 68 36. Multi-threading hands-on and exercise Lecture 69 37. Debugging & Profiling Section 7: Data Engineering Introduction Lecture 70 1. Data Engineering introduction, OLTP & OLAP Lecture 71 2. Data Mart & Data Mesh Lecture 72 3. Data Lake, Data Lakehouse, DWH Section 8: AWS Distributed Storage - S3 (Simple Storage Service) for Data Engineers Lecture 73 1. S3 Introduction 1 Lecture 74 2. S3 Introduction 2 Lecture 75 3. S3 Basics Lecture 76 4. S3 Basics Hands-on Lecture 77 5. S3 Versioning Lecture 78 6. S3 Encryption Lecture 79 7. Storage Class Lecture 80 8. S3 Multipart Upload Lecture 81 9. Lifecycle Policies Lecture 82 10. Cross Region Replication Lecture 83 11. S3 Mountpoint Lecture 84 12. Security - S3 Identity Based Policy Lecture 85 13. Security - S3 Bucket Policy Lecture 86 14. Bucket Policy with VPC, IP address, VPCE Lecture 87 15. S3 Access Point Lecture 88 16. S3 Object Lambda Lecture 89 17. Pre-signed URL Lecture 90 18. S3 Performance Considerations Lecture 91 19. S3 Pricing Lecture 92 20. Architectural Patterns using S3 Section 9: Data Modelling - Normalization, ER Diagram, Dimensional Modelling, Lecture 93 1. Data Modelling Introduction Lecture 94 2. Normal Forms 1NF 2NF 3NF Lecture 95 3. Relations: one-to-one, one-to-many, many-to-one, many-to-many Lecture 96 4. Dimensional modelling - Facts, Dimensions & Grains Lecture 97 5. Grains Exercise Lecture 98 6. Dimensional Modelling Technique Lecture 99 7. Types of Fact & Dimension Tables Section 10: Data Warehouse on AWS - Redshift Infra Lecture 100 1. Redshift Infra Lecture 101 2. Redshift Infra HandsOn Lecture 102 3. Redshift Architecture - Zone Map, Columnar Storage Lecture 103 4. Cluster Resize - Elastic & Classic Lecture 104 5. Cluster Resize - HandsOn Lecture 105 6. Cluster Pause & Rename Lecture 106 7. Snapshot & Backup Lecture 107 8. Redsfhit Infra Conclusion Section 11: Redshift Objects Lecture 108 1. Querying, Connection, RSQL, QEV2 Lecture 109 2. Query Editor & RSQL setup Lecture 110 3. Object Hierarcy, tables hands-on Lecture 111 4. Data Types Hands-on Lecture 112 5. Table operations Hands-on Lecture 113 6. Redshift ACID, Locks, Isolation Level Lecture 114 7. Implement Transactions Lecture 115 8. AccessShareLock & ShareRowExclusiveLock HandsOn Lecture 116 9. Redshift SUPER datatype Lecture 117 10. Section Summary Section 12: Redshift Deep Dive Lecture 118 1. Distribution Key & Style, Sort Key Lecture 119 2. Column Compression Lecture 120 3. Modify Dist Sort Key, Compression HandsOn Lecture 121 4. COPY Command Theory Lecture 122 5. COPY Command HandsOn Lecture 123 6. UNLOAD Command Lecture 124 7. AWS DMS - Move from OLTP to DWH Lecture 125 8. DMS - Setup Source OLTP & Python application Lecture 126 9. Setup DMS Instance, Endpoint, Task Lecture 127 10. DMS Task - OLTP to DWH Lecture 128 11. Table Maintenance - VACUUM & ANALYZE Lecture 129 12. Vacuum & Analyze HandsOn Section 13: Redshift Features Lecture 130 1. Materialized View (MV) Lecture 131 2. MV HandsOn Lecture 132 3. Query Federation Lecture 133 4. Redshift Spectrum Lecture 134 5. Streaming Ingestion Lecture 135 6. Redshift Feature Use Cases Section 14: Redshift Query Tuning Lecture 136 1. Query Execution Lecture 137 2. EXPLAIN Plan & System Joins Lecture 138 3. System Joins HandsOn Lecture 139 4. Data RE-distribution Lecture 140 5. EXPLAIN & RE-distribution HandsOn Lecture 141 6. Query Tuning Exercise - Part 1 Lecture 142 7. Query Tuning Exercise - Part 2 Lecture 143 8. Query Tuning Exercise - Part 3 Section 15: Redshift Workload Management (WLM) Lecture 144 1. WLM Intro & Query Queue Lecture 145 2. Concurrency Scaling, Short Query Acceleration Lecture 146 3. Configure WLM HandsOn Lecture 147 4. Create Query Queue HandsOn Lecture 148 5. Query Queue In Action Lecture 149 6. Concurrency Scaling In Action Section 16: Redshift Security - RBAC, CLS, RLS, Dynamic Data Masking (DDM) Lecture 150 1. Users, Roles, RBAC Lecture 151 2. Users, Roles, RBAC HandsOn Lecture 152 3. Row & Column Level Security (RLS & CLS) Lecture 153 4. Multiple RLS Policies HandsOn Lecture 154 5. CLS HandsOn Lecture 155 6. Combine RLS & CLS HandsOn Lecture 156 7. Dynamic Data Masking Lecture 157 8. Track Users, Roles, CLS and RLS Lecture 158 9. Audit Logging Section 17: Monitoring in Redshift Lecture 159 1. Monitor Redshift using Console Lecture 160 2. System Views for Monitoring Queries, Redshift Objects, Configuration Parms Section 18: Redshift Serverless Lecture 161 1. Introduction to Redshift Serverless Lecture 162 2. Create & Delete Redshift Serverless Resources Lecture 163 3. COPY & UNLOAD in Serverless Lecture 164 4. ZeroETL Integration Setup Lecture 165 5. ZeroETL in Action Lecture 166 6. Query Tuning Similarities Lecture 167 7. Migrate from Provisioned to Serverless Section 19: Detailed Redshift Pricing Lecture 168 1. Redshift Pricing Components Lecture 169 2. Pricing Example - Provisioned, Serverless, Concurrency Scaling, Spectrum Lecture 170 3. AWS Pricing Calculator Section 20: Redshift Additional Information Lecture 171 1. Redshift Integration with AWS Services Lecture 172 2. Redshift & Snowflake Comparison Lecture 173 3. Redshift Best Practices Lecture 174 4. Redshift Limitations and Challenges Section 21: AWS Metadata Repository - Glue Data Catalog Lecture 175 1. AWS Glue Catalog - Theory Lecture 176 2. Glue Catalog - Setup Data Stores & IAM Roles HandsOn Lecture 177 3. Store Aurora metadata in Glue Catalog Lecture 178 4. Store S3 and Redshift metadata in Glue Catalog Section 22: Data Governance using AWS Lake Formation Lecture 179 Lake Formation Introduction Lecture 180 Permission Flow HandsOn 1 Lecture 181 Permission Flow HandsOn 2 Lecture 182 Lake Formation - Tag Based Access Control (LF-TBAC) Lecture 183 LF-TBAC HandsOn Lecture 184 LF - Data Filtering Lecture 185 LF Clean Up (Please complete this) Section 23: Data Lakehouse on AWS - Athena Lecture 186 1. Athena Introduction Lecture 187 2. Athena Intro Hands On Lecture 188 3. Athena SerDe, File & Row format Lecture 189 4. SerDe, Format, CTAS Hands On Lecture 190 5. UNLOAD, Prepare & Execute, Query JSON Lecture 191 6. UNLOAD, Prepare & Execute, Query JSON Hands On Lecture 192 7. Schema Evolution, JSON_EXTRACT Lecture 193 8. Iceberg, ACID Lecture 194 9. Athena Partitioning & Bucketing Lecture 195 10. More DDL Commands Lecture 196 11. Athena WLM Theory Lecture 197 12. Workgroup HandsOn Lecture 198 13. Capacity Reservation HandsOn Lecture 199 14. Performance Tuning Theory Lecture 200 15. Athena Pricing & Performance Tuning Lecture 201 16. Architectural Patterns using Athena Section 24: Big Data Warehouse - Hive Lecture 202 1. Hadoop Theory Lecture 203 2. File Formats Lecture 204 3. Hive Architecture & Components Lecture 205 4. Hive CLI Lecture 206 5. Data Types, databases, tables, File & Row Format, Hive SerDe Lecture 207 6. Hive Databases hands-on Lecture 208 7. Hive Tables hands-on Lecture 209 8. Partitioning & Bucketing Lecture 210 9. Partitioning & Bucketing hands-on Lecture 211 10. Load, insert, ACID, Materialized Views etc Lecture 212 11. JOINs, Locks, Configuration Parameters Data Engineers, Data Scientists, Data Analysts,Python developers, Application Developers, Big Data Developers,Database Administrators (DBA), Big Data Administrators,Solutions Architect, Cloud Architect, Big Data Architect,Technical Managers, Engineering Managers, Project Managers RapidGator NitroFlare UsersDrive -.part09.rar See full article |