AWS Data Engineer Project | Building a Data Pipeline on AWS

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In this video we have covered end to end AWS data engineering project

In this project, we'll cover:

how we can use AWS Glue for creating pipeline ,
how we can trigger AWS Glue using AWS Lambda Function
how we store data using amazon s3
how we can use AWS IAM for policy
how we use AWS Cloudwatch for monitoring

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Please like & share the video.
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Chapters:
0:00 Introduction
2:09 AWS S3
3:15 AWS GLUE Data pipeline
7:42 AWS Lambda creation
9:56 AWS IAM

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script and dataset download :
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PYSPARK PLAYLIST -

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📣Want to connect with me? Check out these links:📣

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what we have covered in this video:

Welcome to our latest project tutorial on building a robust data pipeline using AWS Glue, Lambda, and Amazon S3! In this comprehensive guide, we'll walk you through the process of designing and implementing a scalable and efficient data pipeline architecture leveraging the power of these AWS services.

AWS Glue simplifies the process of preparing and loading data for analytics, AWS Lambda enables serverless data processing, and Amazon S3 provides scalable storage for your data. By combining these services, you can create a flexible and reliable data pipeline to handle various data processing tasks.

In this project, we'll cover:

Architecture Design: We'll start by discussing the design considerations for building a scalable data pipeline using AWS Glue, Lambda, and S3. We'll explore how to architect your solution to handle data ingestion, transformation, and storage efficiently.

Data Ingestion with S3: We'll dive into data ingestion techniques using Amazon S3 as our data lake. We'll demonstrate how to set up S3 event notifications and triggers to automate data ingestion processes, ensuring that new data is processed in real-time.

Data Transformation with Glue: Next, we'll use AWS Glue to perform data transformation tasks. We'll show you how to define Glue jobs to extract, transform, and load (ETL) data from S3, enabling you to cleanse and prepare your data for analysis.

Serverless Data Processing with Lambda: We'll integrate AWS Lambda into our data pipeline to perform serverless data processing tasks. We'll demonstrate how to trigger Lambda functions based on S3 events or schedules, allowing you to process data in real-time or batch mode.

Data Storage and Integration: Once our data is transformed, we'll load it back into Amazon S3 for storage. We'll discuss best practices for organizing and managing data in S3, including partitioning and data lifecycle management.

Monitoring and Optimization: Finally, we'll cover monitoring and optimization techniques for our data pipeline. We'll explore how to use AWS CloudWatch and other monitoring tools to track pipeline performance and optimize resource usage.

By the end of this project, you'll have a solid understanding of how to leverage AWS Glue, Lambda, and S3 to build a scalable and efficient data pipeline that can handle a variety of data processing tasks.

Don't forget to like, share, and subscribe for more tutorials on cloud computing, data engineering, and AWS best practices! Let's dive in and unleash the full potential of AWS for your data projects.
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Hope you liked this video and learned something new :)
See you in next video, until then Bye-Bye!

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[harini]

Hi, Your videos are easy to understand and learn. Thanks a lot for posting

Please make some more videos on Azure, SQL, PowerBi and PySpark 🙂

[balasubramaniamr]

Thank you brother i learnt lot from your videos.. much love ❤

[infygazzy]

Fantastic.. very easy to learn. Thanks for sharing

[mukkaraganeshkumar]

Thank you very much for your videos it's very helpful for me, Can you please let me know that aws glue will be charged even if we are using a free tier account

[pythonenthusiast]

@9:23 how did you come up with that code to write in the lambda function to act as a trigger? pease explain, will he helpful if you create a video on it, or if its easy you can explain in comments

[BOSS-AI-]

8:08 why you create new role for lambda function ? why don't you use previous IAM role that you created for Glue in which you attach all policies for Glue, lambda and S3 ?

[nydarko]

Does this mean that aws glue does not have event trigger capabilities ? Since all the lambda function is doing is calling the glue etl job upon an event trigger

[SiddhantJaiswal-qg]

Where did you git the script for glue to be called from lambda function because in video you have copy pasted it

[idontevenuseyoutubebro]

if we want to convert from json/csv to parquet same procedure just seleect different conversion type?

[therestfulmedia]

We are eagerly waiting your videos sir…! How many total videos will this playlist have ? Any idea

[mandadiashok]

Hi Sir,
I have watched your videos; it's very help full.
I have a quick question, why we need go for lambda to trigger the job, we have option on glue event trigger right? Any specific reason behind this.

Thanks.

[Anna_Tamil]

Hi bro can you make video for step function

[Bhakti-geets-gods]

I got error in cloudwatch log.
In log streams it is saying- " The specified log group does not exist"
What is means ??

[srinivasyadavkalamanda]

Why do we need S3 full access? Don’t think it’s a best practice to grant S3 full access.

[deepanshuaggarwal]

We are directly writing code in AWS lambda. But how companies manage it means can we use github sync here so that we can maintain code changes history also?

[praveerpratap]

Hi, I have a doubt I wanted to make a project related to weather data which is in csv file, I accessed the data from csv file using kafka from producer to consumer that I have done. But after that I wanted to put that data into s3 then wanted to so transformation into data like preprocessing using pyspark then store into another s3 bucket and do the Visualization of that weather data or may try ML for forecasting how can I do that using aws and also want to automate whole process. Can anyone help me out.

[ravitejakavati]

Thanks alot for the video. Very helpful . looking for some more practical projects. Can you please provide your mail id for contacting you.. Thanks..