Canada
Puerto Rico
USA
Belgium
France
UK
India
Client Background
The client is an American media company providing marketing data and analytics to enterprises, media and advertising agencies, and publishers.
Client Need
The client faced escalating costs and operational inefficiencies due to an outdated on-premises infrastructure, hindering their ability to scale and innovate. Key challenges included:
Struggled to extract insights from their live data, limiting their ability to make informed business decisions
Manual processes increased the risk of human error and led to higher operational costs, impacting profitability
Inability to efficiently process incoming incremental data resulted in delayed insights, leading to lost competitive advantage
Solution
We implemented the following solutions:
Cost-Effective Data Processing: Provided a cloud-optimized, on-demand spin-up solution for computation offloading and Snowflake-based reporting solution
Scalable Data Ingestion: Executed Airflow jobs that extracted over 5TB of data weekly from the on-premise MapR cluster and stored it using shell scripts & AWS CLI
Resource Optimization: Provisioned an AWS EMR cluster and scaled to data size, using CloudFormation templates & AWS CLI to execute Spark & Pig scripts
Accessible Data Storage: Moved resultant post-processing data from EMR into S3 buckets for storage
Operational Efficiency: Automated AWS EMR cluster scaling, which enabled termination upon completion of processing
Realized Benefits
The solutions implemented yielded the following benefits:
Enabled a cost-efficient, on-demand computation on the AWS platform
Added value by optimizing resource utilization through tailored recommendations for resource type and configuration, ensuring a cost-effective and optimal solution
Accelerated data processing time from 48 hours to 24 hours by migrating on-premises jobs to the cloud
Tools & Technologies
Amazon S3
Apache Pig
Apache Spark
Cloud Formation
Amazon EMR
MAPR
Apache Airflow
Python
R
Powershell
Snowflake
Bash
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