Data-Driven Decisions: Self-service BI solution

In a world where digitization accelerates with each passing day, businesses constantly seek powerful insights to propel them toward unparalleled growth.

We were privileged to collaborate with a visionary client who sought to revolutionize their in-house self-service BI solutions, using AWS to unlock the full potential of their data and empower decision-makers with cutting-edge analytical capabilities.

Challenge Overview

Our client stood at a pivotal juncture, eager to break away from the traditional, costly BI tools dominating the market. Their vision was ambitious: to harness their extensive data repository within a global meta store service, hosted on an AWS S3 data lake, through a groundbreaking and user-friendly web application. This application was designed to empower Business Analysts, enabling them to effortlessly search, filter, and query vast datasets, unlocking superior analytics and actionable insights. The task was clear—a system that was not only flexible but also resilient, a solution that allowed dynamic SQL query creation through intuitive drag-and-drop operations, all underpinned by a robust microservice architecture.

Market Drivers:

Data Explosion: The exponential surge in data generated by businesses demands advanced tools for comprehensive analysis and visualization, making it essential for organizations to harness this data effectively.

Shifting Business Landscape: As industries evolve, data-driven decision-making is increasingly becoming a cornerstone for maintaining a competitive edge, emphasizing the need for robust BI solutions.

Cloud Adoption: The shift to cloud-based BI solutions offers unparalleled scalability, cost-efficiency, and accessibility, catering to businesses of all sizes and enabling them to manage their data more effectively.

Advanced Analytics: The integration of AI and machine learning into BI tools is driving more sophisticated data analysis, enhancing predictive capabilities, and providing deeper insights.

Growth Trends:

Self-Service BI: The rise of user-friendly BI tools is democratizing data insights by empowering business users to independently analyze data, breaking down barriers between data and decision-making.

Embedded Analytics: The trend of integrating BI functionalities directly into business applications is allowing for seamless data exploration and real-time analysis, making insights more accessible and actionable.

Prescriptive Analytics: As BI tools continue to evolve, they are moving towards offering prescriptive recommendations, guiding businesses on the best course of action based on data analysis, thereby driving more informed decision-making.

Solution built with vision:

Our dedicated team embarked on the mission to turn this vision into tangible reality.

We committed to a Java Spring Boot framework to develop a highly scalable backend, fortified with JWT-based authentication. Containerization was key; our solution thrived in the AWS Elastic Container Service (ECS), integrated with load balancers, with each resource meticulously managed through Terraform. The service backend kept track of each user’s performance jobs on the platform, also allowing them to resume jobs which had failed or been canceled. The solution allowed users to maintain each self-served asset as a custom project in the platform.

Our web application engineers, meanwhile, harnessed the agility of React and TypeScript to birth a web application, featuring a bespoke filter widget. This innovative tool allowed users to assemble their queries by simply dragging and dropping columns, crafting custom SQL queries that derives the future insight on the business data.

As the sequence of SQL queries took life, AWS Elastic MapReduce (EMR), intricately connected to the a meta store, orchestrated their execution, processing data with clinical precision. To ensure performance we did a level of optimization on Apache Spark configuration and codebase to support unprecedented large datasets. We utilized Hive metastore’s internal MySQL DB to query the table metadata. This allowed users to harness the SQL tool to generate targeted date query.

The Technology Stack:

Java Spring Boot Microservice: The backbone, providing service discovery and authentication.

Terraform, AWS ECS, and ECR: The foundation, ensuring smooth, secure orchestration of services.

Jenkins, AWS SES, and SNS: The lifeblood of continuous integration and proactive notifications.

AWS EMR with Cloud Formation Templates: The engine, driving Hadoop’s Big Data processing with finesse.

Apache Spark and Java: The brain, adeptly querying data to extract meaningful patterns.

AWS Cognito and Amplify: The gatekeepers, managing user access and flawlessly hosting our solution.

TypeScript and React: The interface, offering an engaging, role-managed user experience.

Key Business Takeaways:

Through our collaboration, we didn’t just deliver a solution; we laid the foundation for a revolution in BI web applications. The true brilliance of this journey lies not just in the destination, but in every innovative step we took to get there.

Businesses worldwide, much like our client, have the power to shape their futures through similar technological integrations. Imagine a world where in-house analytics provide not only insight but strategic foresight, fueled by scalable microservices, advanced big data solutions, and the flexibility of cloud technology. By embracing data-driven strategies, understanding market trends, overcoming challenges, and focusing on user-centric designs, companies that develop innovative BI solutions will play a pivotal role in shaping the future of data analytics.

At Athergo together, let’s harness the power of technology to unlock the rich, data-driven insights of tomorrow. Empower your business’s potential today, and step confidently into a future of boundless opportunities.