Birlasoft builds an Enterprise Data Hub for a Client, enabling real-time analytics and data-driven decision-making.
The Challenge
Building an enterprise-level central data repository to enable multifunction analytics presents several challenges. One is the complexity of integrating data from various sources. Additionally, managing the scalability and performance of the data repository is a daunting task. Data security and privacy considerations, along with the need for comprehensive data governance and access control, add to the complexity of establishing an effective and reliable central data repository for multifunction analytics.
Creating a specific program to enable easy data sharing from multiple businesses in one location presents several challenges. Key among them is integrating data from diverse sources. Additionally, addressing data privacy and security concerns becomes crucial when dealing with sensitive information from multiple entities. Developing a user-friendly interface that allows seamless data sharing and collaboration while maintaining data governance and access controls requires overcoming technical, operational, and regulatory hurdles.


The Solution
As part of the solution, an Enterprise Data Hub (EDH) was created to establish an enterprise-level Central Data Repository facilitating multifunction analytics. This repository enabled the organization to consolidate and manage diverse datasets from various sources, including QWP/Track-wise systems and on-premise data sources. Complex data modeling techniques were employed to integrate and harmonize the data. The EDH provided a unified and scalable data storage, processing, and analysis platform, enabling stakeholders to derive valuable insights and make data-driven decisions. The solution helped the organization gain a comprehensive view of its data, improving its analytics capabilities and enhancing operational efficiency.
The solution implemented an ETL flow to extract data daily from the QWP/Track-wise application. This data, stored in AWS S3, allowed for the storage of current and historical datasets in a scalable and cost-effective manner. AWS Glue jobs were developed to facilitate data transformation and integration, and Glue Crawler was used to automatically discover and catalog the data. By leveraging AWS Glue's capabilities, the organization achieved streamlined and automated data processing, ensuring data accuracy, consistency, and accessibility for downstream analytics and reporting purposes. The solution enabled the organization to leverage the power of AWS services for data management and analysis.
The solution included migrating data to Snowflake, a scalable and efficient cloud-based data warehouse. The data was flattened to enhance consumption, simplifying its structure and making it more accessible for analysis. This allowed stakeholders to navigate and retrieve the necessary information for decision-making easily. Additionally, reports were prepared using Tableau, a powerful visualization tool, to showcase trends and highlight key performance indicators (KPIs). These reports provided valuable insights, enabling stakeholders to make informed decisions based on real-time data analysis. The combination of Snowflake's data capabilities and Tableau's reporting functionalities empowered the organization to gain actionable insights and drive business growth.
Liked this transformation story?
Let's build yours now.
The Impact
The implemented solution provided efficient and cost-effective storage for managing vast amounts of data. It also ensured the storage of high-quality data without compromising data integrity. The solution enabled the organization to stream real-time data and leverage cutting-edge technologies for timely insights and decision-making. The solution also allowed the organization to address quality complaints swiftly. Overall, the solution offered an impactful approach to data storage, real-time capabilities, and quality management.
The implemented solution significantly enhanced data processing capabilities, enabling the organization to handle large volumes of data in shorter timeframes. The solution also ensured data security and availability of critical data assets, thereby improving overall efficiency. Additionally, it delivered best-in-class processing speeds, allowing the enterprise data hub (EDH) program to operate at peak performance. Overall, the implemented solution unlocked new levels of efficiency and value for the organization.
The implemented solution revolutionized the enterprise data hub (EDH) quality by offering low-cost cloud solutions. Leveraging Snowflake's capabilities, the solution seamlessly integrated with the AWS ecosystem, enabling real-time analytics and data-driven decision-making. The solution streamlined operations while ensuring a strong security model, safeguarding sensitive data. With Snowflake's cost-effectiveness, scalability, and security, the implemented solution delivered exceptional value, enabling the organization to drive innovation and achieve business goals.