Data and Analytics
We help companies with their engineering needs in software development and help adopt cloud native technologies to make their infrastructure robust and scalable.
October 28, 2024
Several customers, ranging from global retail enterprises to financial services and healthcare organizations, approached AIN to modernize their outdated data warehouse systems. These clients were struggling with slow reporting, inefficient data processing, and limited scalability. Their legacy data warehouse infrastructure, which relied on on-premise solutions, was no longer able to meet the growing demands of data processing, reporting, and analytics.
AIN delivered a unified solution, migrating their data warehouses to modern, cloud-based infrastructures and integrating advanced reporting tools to streamline data access, improve reporting speed, and empower self-service reporting for business users.
Clients were facing significant delays in generating reports due to slow query processing and the inability to handle large volumes of data efficiently. These delays hindered decision-making and operational efficiency.
Legacy reporting tools lacked real-time analytics, were difficult to use, and required heavy reliance on IT teams for report generation. This created bottlenecks, preventing business users from quickly accessing the data they needed.
Existing on-premise systems were not built to scale dynamically, leading to performance issues during peak usage and increasing maintenance costs as data volumes grew.
AIN delivered a robust data warehouse modernization solution tailored to the needs of multiple clients. The solution focused on migrating from legacy, on-premise data warehouses to scalable, cloud-based environments, optimizing reporting tools, and improving overall data processing efficiency.
AIN delivered a robust data warehouse modernization solution tailored to the needs of multiple clients. The solution focused on migrating from legacy, on-premise data warehouses to scalable, cloud-based environments, optimizing reporting tools, and improving overall data processing efficiency.
AIN migrated the clients' data warehouses to cloud platforms such as Amazon Redshift and Google BigQuery, enabling each business to handle growing data volumes more effectively. The cloud infrastructure offered scalability on demandand significantly reduced infrastructure costs.
We implemented automated ETL pipelines using tools like AWS Glue and Apache Airflow, ensuring that data was ingested, transformed, and loaded in real time. This automation eliminated manual data processing efforts and ensured up-to-date data availability for reporting.
Advanced reporting tools such as Power BI and Tableau were integrated into the new data environments, giving clients the ability to generate real-time reports, create custom dashboards, and access key insights independently without relying on IT support.
For clients needing real-time data access, AIN implemented streaming solutions using Amazon Kinesis and Apache Kafka, allowing real-time data processing and immediate access to up-to-date reports. This capability significantly improved decision-making speed across multiple business areas.
We ensured that the cloud infrastructure was both scalable and secure, using services like AWS Identity and Access Management (IAM) and Google Cloud Security to maintain strict data governance and compliance standards.
Across multiple clients, report generation times were drastically reduced, from hours or days to just minutes. This allowed key stakeholders to pull critical reports almost instantly, empowering them to make informed decisions quickly.
With the implementation of modern reporting tools, clients across industries were able to move from IT-dependent reporting to self-service models. This improved productivity and allowed teams to focus on data analysis and strategy rather than waiting for reports.
Real-time data processing allowed business users to access live data insights, significantly enhancing the quality and speed of their decision-making processes. This led to improved operational efficiency and responsiveness to market changes.
By migrating to cloud-based data warehouses, clients reduced their total infrastructure and maintenance costs by up to 50%. The ability to scale dynamically based on data usage needs ensured that they could handle peak demand without worrying about performance or downtime.
Automated ETL processes and real-time data synchronization improved the accuracy and consistency of data across all reports, ensuring that teams could trust the data and make decisions with confidence.
Clients were able to generate insights faster, allowing them to react more quickly to changes in the market, customer preferences, and operational demands. This agility provided a competitive edge across multiple industries.
AIN’s data warehouse modernization solution has transformed the way multiple clients across various industries manage, process, and report on their data. By migrating to cloud-based infrastructures, implementing automated data pipelines, and enhancing reporting tools, these clients were able to reduce costs, improve reporting speed, and increase data accuracy. With scalable, real-time access to data, these businesses are now better equipped to make fast, informed decisions that drive growth and innovation.
Agriculture
Project Overview An agricultural-based customer, a global leader in agricultural machinery and financial services, approached AIN to modernize their legacy Debt Manager System, which was running on an aging mainframe infrastructure. The system, critical for managing loan portfolios, debt servicing,...
October 28, 2024
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