Generative AI Driven Data Management for Chemical Manufacturing

Key Highlights

  • Addressed legacy infrastructure constraints and data latency challenges in the client’s on-premises data warehouse, hindering scalability, agility, and timely decision-making.
  • The client faced limitations in scalability, flexibility, and agility with on-premises data warehouse, coupled with data latency issues impacting market responsiveness and operational efficiency.
  • We migrated on-premises data to AWS S3 using AWS DMS, efficiently structuring it into delta tables with Databricks, and ensuring real-time data consistency through CDC.
  • Streamlined operations with enhanced data accessibility and reliability, empowering stakeholders with actionable insights through Tableau, and realized significant cost savings.

Problem Statement

01

Legacy infrastructure constraints: On-premises data warehouse limitations hindered scalability, flexibility, and agility, leading to high management costs.

02

Data latency challenges: Delays in stored data accessibility hampered timely decision-making, impacting market responsiveness.

03

.Integration and Infrastructure Issues: Challenges with system integration, non-cloud apps, and infrastructure cause operational fragmentation, downtime, and user dissatisfaction.

Solution Overview

01

OptiSol partnered with the Canadian fertilizer company to transition on-premises data to AWS S3 Bucket via AWS DMS, streamlining data management.

02

Leveraging Databricks notebooks, data was structured and transformed for efficient storage in delta tables on AWS S3, enhancing accessibility.

03

AWS DMS facilitated Change Data Capture (CDC) from the on-premises database, ensuring data consistency and minimizing processing overhead.

04

Tableau dashboards were developed using Data Lake-derived Sales Report data, empowering stakeholders with actionable insights.

05

The cloud-native solution ensured scalability, manageability, and improved performance, enabling cost savings and fostering innovation opportunities.

Business Impact

01

Efficient Data Migration: On-premises data was migrated to AWS S3 using AWS DMS, ensuring simplified and consistent data management.
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Improved Operational Efficiency

02

Improved Data Handling: Databricks transformed and structured the data into delta tables on AWS S3, enhancing accessibility and ensuring robust reliability.
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Enhanced Data Structuring

03

Cloud Analytics: The cloud-enabled Tableau dashboards for sales reports improved performance, scalability & cost efficiency, providing valuable insights.
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Improved Cost Efficiency

ABOUT THE

Project

This project implements a transformative solution for a Canadian fertilizer company facing challenges with legacy on-premises data infrastructure. By migrating their data to AWS S3 via AWS Data Migration Service (DMS) and leveraging Databricks for efficient data structuring and transformation, we streamlined their operations and enhanced data accessibility. Change Data Capture (CDC) ensured data consistency, while Tableau dashboards from Data Lake-derived Sales Report data empowered stakeholders with actionable insights. Our cloud-native approach not only improved scalability, manageability, and performance but also reduced costs and fostered innovation, revolutionizing their data handling and operational efficiency.

Tech Stack

Testimonials of Our Happy Clients

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