kingers Posted May 26 Report Share Posted May 26 Data Processing with Spark Kafka (Data Engineering Vol2 AWS) Published 4/2025 Duration: 3h 35m | .MP4 1280x720, 30 fps(r) | AAC, 44100 Hz, 2ch | 1.28 GB Genre: eLearning | Language: EnglishBatch & Stream Processing using Spark and Kafka on AWS What you'll learn - Deep dive on Spark and Kafka using AWS EMR, Glue, MSK - Understand Data Engineering (Volume 2) on AWS using Spark and Kafka - Batch and Stream processing using Spark and Kafka - 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.) - AWS Data Analytics services - S3, EMR, Glue, MSK Requirements - Good to have AWS and SQL knowledge Description This isVolume 2 of Data Engineeringcourse. In this course I will talk about Open Source Data Processing technologies -Spark and Kafka, which are the most used and most popular data processing frameworks forBatch & Stream Processing. In this course you will learnSpark from Level 100 to Level 400 with real-life hands on and projects.I will also introduce you to Data Lake on AWS (that is S3) & Data Lakehouse usingApache Iceberg. I will use AWS as the hosting platform and talk about AWS Services likeEMR, S3, Glue and MSK. I will also show you Spark integration with other services likeAWS RDS, Redshift and DynamoDB. You will get opportunities to do hands-on using large datasets (100 GB - 300 GB or more of data).This course will provide you hands-on exercises that match with real-time scenarios like Spark batch processing, stream processing, performance tuning, streaming ingestion, Window functions, ACID transactions on Iceberg etc. Some other highlights: 5 Projects with different datasets. Total dataset size of 250 GB or more. Contains training of data modelling -Normalization & ER Diagramfor OLTP systems.Dimensional modellingfor OLAP/DWH systems. Other technologies covered - EC2, EBS, VPC and IAM. Optional Python Course Who this course is for: - Python developers, Application Developers, Big Data Developers - Data Engineers, Data Scientists, Data Analysts - Database Administrators, Big Data Administrators - Data Engineering Aspirants - Solutions Architect, Cloud Architect, Big Data Architect - Technical Managers, Engineering Managers, Project Managers More Info Please check out others courses in your favourite language and bookmark them - - - -DDownloadhttps://ddownload.com/euu1ghr78j2g/yxusj.Data.Processing.with.Spark.Kafka.Data.Engineering.Vol2.AWS.part1.rarhttps://ddownload.com/zfdi2w60q5xc/yxusj.Data.Processing.with.Spark.Kafka.Data.Engineering.Vol2.AWS.part2.rarRapidGatorhttps://rapidgator.net/file/4830df5364a9b4e12e8b62ea658508dc/yxusj.Data.Processing.with.Spark.Kafka.Data.Engineering.Vol2.AWS.part1.rarhttps://rapidgator.net/file/c43ad1d64c300b3501bfe13e0d3bef8e/yxusj.Data.Processing.with.Spark.Kafka.Data.Engineering.Vol2.AWS.part2.rarNitroFlarehttps://nitroflare.com/view/309769A5273F626/yxusj.Data.Processing.with.Spark.Kafka.Data.Engineering.Vol2.AWS.part1.rarhttps://nitroflare.com/view/DA73D4FEF8CBC69/yxusj.Data.Processing.with.Spark.Kafka.Data.Engineering.Vol2.AWS.part2.rar Link to comment Share on other sites More sharing options...
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