Optimize ETL Pipelines with AWS Lambda: The Power of Cloud Data Engineering

 

Navigating the Data Landscape

From the age of information, we’re transcended to the age of data. Nothing has changed apart from the term, since data is information. Every day there are 328.77 million terabytes of data are produced, and the one who learns to draw insights from data is the early bird who catches the worm. 

The vast landscape of data plays a crucial role in decision-making across industries, consolidating these insights to power the growth of businesses in multiple directions. Businesses can benefit from professional Data Engineering services to consolidate and process their essential data, enabling informed decision-making.

Useful Tip: See data as a gold mine of insights—harness it to make informed business decisions. 

ETL: The Key to Data Consolidation

Consider any business organization; it would consist of various departments, for example, production, marketing, design, retail, IT, accounts HR, etc., all working in unison towards a north star metric. Every department generates essential data that needs to be consolidated and processed to a data warehouse that can power your analytics and predictive modeling. 

The magic spell to extract, transform, and load (ETL) this data into the warehouse is what data engineers work with. It's like using a magic wand to capture data, decipher its alien language, and finally gather them into your data warehouse. Of course, gathering all this data on cloud comes with a cost you don’t necessarily have to bear. ELT services are crucial in extracting, loading, and transforming data, enabling efficient consolidation and analysis.

Exploring the concept of data engineering helps businesses grasp its significance in harnessing and extracting insights from data. Maybe you simply don’t have that much data to play with compared to the cost you’re paying. For smaller data volumes that require less than 15 minutes of ETL, there isn’t a need for expensive ETL tools. This is when AWS Lambda becomes the cost-effective choice for your ETL Needs.  

Useful Tip: ETL is your consolidation tool to unify data from all departments. Tailored Data Engineering solutions empower businesses to effectively consolidate, process, and derive insights from their diverse data sources.

AWS Lambda: Your Go-to for ETL 

AWS Lambda is a serverless service that Amazon Web Services (AWS) provides. It lets you run code without needing to manage servers and supports multiple programming languages (Python, Node.js, Java, C#, Ruby, Go, and Power Shell, to name a few), giving you the flexibility to use the one that suits your needs. 

Leveraging AWS Lambda, a cloud Data Engineering service, provides scalable and efficient data processing capabilities. Let's explore further the benefits of using AWS Lambda.

  • Customization and control are at your fingertips with AWS Lambda, allowing you to craft personalized scripts, define memory allocation, runtime, and timeout durations, and even tweak memory architectures. Plus, enabling VPC for secure connections is straightforward.

  • Schedule flexibility is a crucial Lambda feature - you can trigger functions at specific times or at regular intervals (e.g., every 10 minutes, 3 hours, 24 hours), all facilitated by the AWS Eventbridge service.

  • Integration is a breeze with Lambda - it seamlessly interacts with other AWS services, such as Comprehend, RDS, and S3, directly from within your function's code.

  • Monitoring your Lambda functions is hassle-free, keeping you informed about crucial metrics like memory consumption and the status of function executions (failed or successful).

  • Configuration flexibility allows Lambda functions to utilize environment variables and incorporate external libraries via zip packages.

  • Cost-effectiveness is a significant advantage with AWS Lambda - you're only billed for the actual compute time used by your functions.

  • Budget-friendly options are plentiful with AWS, as they offer a free tier, and their pricing model is based on the number of requests and the compute time used. This makes Lambda the go-to choice economically thinking.

Useful Tip: An effective ELT solution simplifies the process of extracting, loading, and transforming data into a centralized warehouse for further analysis.

ETL Pipeline


Useful Tip: AWS Lambda is a flexible and adaptable ETL tool—use it to run code cost-effectively.

ETL Pipeline Architecture

Let's use Facebook as an example. Facebook provides a Graph API for developers to extract and analyze data. With a Lambda function, you can automate extracting relevant data, such as your daily ad spend and the return on ad spend (ROAS). 

For example: If you come up with a business question, how much is your business spending on Facebook Ads every day? What is the return on ad spend ROAS? This information can easily be extracted through Facebook Graph API. Python or any other language code supported by Lambda can be developed and automated to trigger at a specific time or rate.

Useful Tip: A well-architected ETL pipeline can extract, transform, and load data smoothly and efficiently.

IAM, or Identity and Access Management, is an identity you can create in your AWS account with specific permissions. IAM role should be given permissions so that the Lambda function can access Systems Manager. System Manager helps us store some API credentials that should not be exposed inside the code. Event Bridge triggers the Lambda function at a specific time via a cron job or at a specific rate.

Relevant data can be easily transformed and saved in any data warehouse or a destination database, for example, SQL Server or MySQL.

Any change in data capture logic can be applied to check out if any previous data is changed from the source and can be compared with destination data and identified easily. 

Useful Tip: Make sure all this execution needs to be done within 15 minutes of the time interval.

Deployment of Lambda Functions

Lambda functions can use prebuilt libraries available in Lambda Layers (so you don’t need to install libraries inside the code at run time; it won’t work). For example, Python's popular 'Pandas' library is readily available in AWS Layers. Additionally, you can create custom packages for libraries specific to your Lambda function.

Useful Tip: This custom package can be easily created by extracting the .whl files of the required libraries and merging them all together in one place.

Data Pilot - Your Companion in the Data Journey

Data Pilot utilizes AWS Lambda to extract data from various sources such as Facebook, Instagram, Google Ads, Google Analytics, Shopify, Magento, SAP, MySQL, SQL databases, and more. We've helped businesses across multiple industries, including fashion, logistics, and enterprise sectors, to harness their data for sales, marketing, and analytics. Expert data engineering consultants like us provide valuable guidance and support to businesses in optimizing their data workflows and strategies.

Data Pilot provides expert Data Engineering consulting with the goal to ensure that our insights and tools inform and drive conversion and business growth. Join us as we continue to navigate the data landscape, turning data into actionable insights. 

Most Useful Tip: Transform your data into insights and actions with Data Pilot.

Written By: Muhammad Irfan Umar & Shaafay Zia

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