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In this video I have talked about salting in spark
Project details for resume :-
.Successfully led a data engineering project in a retail environment using technologies such as Apache Spark, Python, SQL, and Amazon S3 to optimize data processing.
.Implemented structured data models, including dimension and fact tables, to provide valuable context for point-of-sale data analysis.
Designed and executed an incentive program based on sales performance, enhancing motivation among sales teams by rewarding top performers.
Managed extensive daily data volumes of approximately 100GB, demonstrating the ability to handle large-scale data pipelines.
Employed Spark optimization techniques like caching and broadcast joins to improve data processing speed and efficiency.
Utilized Azure CI/CD pipelines for code deployment, and orchestrated workflows using Airflow and CRON jobs.
Detailed writeup to explain more during interview:-
As a Data Engineer on a project for a prominent offline grocery and kitchen supplies retailer, I applied my expertise in data engineering to drive critical improvements in their data processing and analysis operations.
The project primarily focused on processing and analyzing point-of-sale data, which was structured into dimension and fact tables to provide meaningful context for sales analysis. To further enhance employee motivation and performance, we designed and implemented an incentive program that rewarded salespeople with the highest sales volumes in each store.
Handling a substantial daily data volume of approximately 100GB, we leveraged Apache Spark and applied optimization techniques like data caching and broadcast joins to significantly accelerate data processing. This not only improved the speed of our data pipelines but also increased the efficiency of our data analysis.
We seamlessly integrated the code deployment process into the Azure CI/CD pipeline. As part of workflow automation, we orchestrated task scheduling using Airflow and CRON jobs.
One of the project's major achievements was the implementation of a customer engagement strategy that identified infrequent buyers and provided incentives in the form of coupons. This initiative not only boosted customer retention but also had a positive impact on the overall business growth.
For more queries reach out to me on my below social media handle.
My Gear:-
My PC Components:-
Project details for resume :-
.Successfully led a data engineering project in a retail environment using technologies such as Apache Spark, Python, SQL, and Amazon S3 to optimize data processing.
.Implemented structured data models, including dimension and fact tables, to provide valuable context for point-of-sale data analysis.
Designed and executed an incentive program based on sales performance, enhancing motivation among sales teams by rewarding top performers.
Managed extensive daily data volumes of approximately 100GB, demonstrating the ability to handle large-scale data pipelines.
Employed Spark optimization techniques like caching and broadcast joins to improve data processing speed and efficiency.
Utilized Azure CI/CD pipelines for code deployment, and orchestrated workflows using Airflow and CRON jobs.
Detailed writeup to explain more during interview:-
As a Data Engineer on a project for a prominent offline grocery and kitchen supplies retailer, I applied my expertise in data engineering to drive critical improvements in their data processing and analysis operations.
The project primarily focused on processing and analyzing point-of-sale data, which was structured into dimension and fact tables to provide meaningful context for sales analysis. To further enhance employee motivation and performance, we designed and implemented an incentive program that rewarded salespeople with the highest sales volumes in each store.
Handling a substantial daily data volume of approximately 100GB, we leveraged Apache Spark and applied optimization techniques like data caching and broadcast joins to significantly accelerate data processing. This not only improved the speed of our data pipelines but also increased the efficiency of our data analysis.
We seamlessly integrated the code deployment process into the Azure CI/CD pipeline. As part of workflow automation, we orchestrated task scheduling using Airflow and CRON jobs.
One of the project's major achievements was the implementation of a customer engagement strategy that identified infrequent buyers and provided incentives in the form of coupons. This initiative not only boosted customer retention but also had a positive impact on the overall business growth.
For more queries reach out to me on my below social media handle.
My Gear:-
My PC Components:-
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