Banking & Financial Services
ETL Migration & Conversion BTEQ Conversion
Macro Conversion Fast Load Conversion
Fast ExportStored procedure
View ConversionSchema Conversion
SQL Query ConversionCustomer 360
Data Product(Data Hub)
Project Overview
Our client's journey of transforming their data analytics platform, addressing key challenges, implementing advanced technologies, and achieving measurable business impacts. Migration of a large-scale Teradata data warehouse, with 5 petabytes (PB) of data and 200,000 database objects, from an on-premises environment to Google Cloud Platform (GCP).
Business Impacts
20% Faster Processing
Data processing time was reduced by 40%, enabling quicker decision-making. after conversion of datastage jobs to pyspark and Cloud Data Fusion.
30% Less Manual Work
Automation reduced manual efforts by 30%, freeing up resources for strategic initiatives. Our Code Converter tools convert 200K object to biqquery sql, pyspark and Airflow
22% Cost Reduction
Infrastructure costs were cut in half by leveraging cloud-based solutions.
Real-time Analytics
Implemented real-time data analytics to improve decision-making speed.
Customer Key Facts
Industry
Banking & Financial Services
Location
UK/Europe
Company Size
90000+ Employees
Challenges
Our client faced significant challenges in handling large volumes of data, leading to delayed insights and inefficient processes. They also needed a scalable solution to accommodate future data growth and maintain compliance with strict regulatory requirements.
Tools/Technologies Used
Migration Approach
Handling Huge Teradata Objects
Migrating large Teradata objects required a meticulous approach to ensure data integrity and performance. We implemented a phased migration strategy to handle the complex data structures and minimize disruptions using our code converter tool.
ETL Migration
Transitioning from DataStage jobs to a more modern ETL solution was essential. We re-engineered the ETL workflows to leverage Google Cloud Data Fusion, Dataflow, dataproc and airflow, ensuring efficient data processing and transformation.
Data Reconciliation
To address discrepancies and ensure data accuracy, we performed comprehensive data reconciliation. This involved validating migrated data against source systems to confirm consistency and reliability. developed 20+ dashboard to monitor data reliability.
Consumer-Driven Migration
Our migration strategy was designed with a focus on the end user's needs. We implemented a data hub approach to streamline data consumption and provide users with timely and accurate insights.
Results
By leveraging modern cloud infrastructure and advanced analytics platforms, the client was able to significantly improve operational efficiency, reduce costs, and enhance their data-driven decision-making capabilities.