top of page

Letting Data Speak!

Case Study

Modernizing Data Ingestion for Green Energy AI

A provider of AI-based Green Energy solutions serving 40+ utility companies in electricity generation and distribution.

About the Client

A provider of AI-based Green Energy solutions serving 40+ utility companies in electricity generation and distribution.

Untitled design - 2024-09-27T104509.589.png

Challenge

The client faced the complex task of ingesting data from various tenants with legacy systems into a modern data warehouse. This process needed to align with the latest data warehouse specifications efficiently and effectively while maintaining data integrity and accuracy throughout the transition.

Untitled design - 2024-09-27T105551.128.png

Key Results

  • Reduced pipeline creation time by 40% through the implementation of the pipeline_builder library for automating the pipeline creation process.

  • Reduced onboarding time for a new tenant by 50% (8 weeks to 4 weeks)

  • Improved data accessibility and reliability for 40+ utility companies

  • Streamlined pipeline creation process, reducing manual coding efforts by 80%

Solution

To address the challenge, JashDS developed a robust tool called the pipeline_builder library. The solution involved:

  • Defined a standard template to capture data mapping rules

  • Designing an intelligent pipeline_builder library that can create data pipelines by translating data mapping rules into boilerplate pipeline code.

  • The automation covered 80% to 90% of standard mapping rules like renaming data columns, extracting data from a field using regex, etc. The remaining 10 to 20% of customization was the manual coding effort required by the pipeline developers.

  • Developing ingest, export, and master jobs to automate and streamline data processing.

  • Developed automated test cases from the data mapping rules. These are executed as part of the nightly integration tests and have identified several regression issues till now.

Untitled design - 2024-09-27T104509.589.png

Technologies Used

  • GCP - Google Cloud Storage, Dataflow, Composer (Airflow), Cloud Functions

  • Matillion

  • CircleCI

Other Case Study Items

Analytics SaaS Platform for the Hospitality Industry

Analytics SaaS Platform for the Hospitality Industry

JashDS developed a scalable, multi-tenant SaaS analytics platform for a hospitality client, consolidating data from disparate management systems and reducing data processing time by 75%. The solution incorporated advanced ETL pipelines, a secure data warehouse, and interactive dashboards, enabling rapid, data-driven decision-making across multiple hotel properties.

Enhancing Chat Bot Interactions Accuracy for Healthcare Platform

Enhancing Chat Bot Interactions Accuracy for Healthcare Platform

JashDS enhanced a healthcare platform's chatbot accuracy by 10% by implementing an advanced data ingestion and analysis pipeline, leveraging Azure and Medallion architecture to process 5 GB of daily conversation data and deliver optimized Power BI reports.



Revolutionizing Data Infrastructure for AI-Driven Green Energy Solutions

Revolutionizing Data Infrastructure for AI-Driven Green Energy Solutions

JashDS revolutionized a green energy tech company's data infrastructure by implementing a scalable Matillion-based ETL solution and automated CI/CD processes, resulting in 2-3x faster client onboarding and a 35% reduction in Google Cloud costs. The comprehensive solution included reusable components, optimized SQL queries, and efficient data aggregation techniques, enhancing the client's ability to process vast amounts of utility data from 40+ companies and support their AI-driven green energy initiatives.

bottom of page