Case Study

An Advanced Inventory Management System


Company Overview

Implementing an Efficient Inventory Management System with Tridhya Tech’s Expertise

Unlock the power of data for smarter inventory control!

Our client approached Tridhya Tech to develop an advanced Inventory Management System. They wanted to update their Enterprise Data Warehouse (EDW) architecture and stay competitive by using Hadoop Big Data Technologies to establish an Enterprise-wide Data Hub (EDH). The client's primary objectives were to efficiently ingest, process, and deliver data for analysis, as well as to have a user-friendly dashboard displaying key performance indicators (KPIs) based on the collected data.

Business Challenges

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    Integration of Diverse Data Sources

    Tridhya Tech faced the challenge of integrating data from various sources, including flat files and traditional database systems like Oracle, Teradata, and MySQL, into the Hadoop-based Inventory Management System.

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    Handling Delta Feeds and Supporting Real-Time Use Cases

    Another challenge faced by Tridhya Tech was efficiently loading delta feeds into the Inventory Management System’s data ingestion framework and scheduling them using Oozie. Our team also needed to design the application framework to support real-time use cases in the next phase of the project seamlessly.

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    Data Accessibility and Visualization

    It was challenging for Tridhya Tech to provide access to the ingested data using Hive, which enabled analysts to access and analyze it for further insights. Additionally, our team needed to develop a lightweight web interface dashboard to display key performance indicators (KPIs) based on the acquired data.


Business Solution


Seamless Data Ingestion from Various Sources Using Sqoop

Tridhya Tech implemented Sqoop, a tool for efficiently transferring data between Hadoop and external data sources. By utilizing Sqoop, our team seamlessly ingested data from various systems into the Hadoop cluster, establishing a unified data repository for the Inventory Management System.


Managed Delta Feeds and Enabled Real-Time Capabilities

Tridhya Tech developed a robust data ingestion framework that effectively managed delta feeds and scheduled processes using Oozie, ensuring timely data updates in the Inventory Management System. Additionally, the team incorporated flexible and scalable architecture patterns, such as stream processing frameworks and event-driven architectures. These could support real-time use cases and enable a smooth transition into real-time data processing.


Data Accessibility and Visualization with Hive for a User-friendly Dashboard

Tridhya Tech executed Hive, a data warehousing, and SQL-like query language, to expose the ingested data to analysts. This enabled easy access and querying of the data for advanced analytics and reporting. Additionally, Tridhya Tech developed a user-friendly web interface dashboard that presented the KPIs in a visually appealing and intuitive manner. The dashboard provided a consolidated view of the data and allowed analysts to make data-driven decisions efficiently.

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Tridhya Tech successfully delivered the Inventory Management System, which included an online Business Analysis Tool. The client was able to automate their data ingestion process, generate combined reports from all subsystems, and analyze data significantly faster compared to their traditional Data Warehouse (DWH) setup. The developed application framework was designed to support real-time use cases in future project phases, providing the client with scalability and adaptability. Overall, Tridhya Tech's Inventory Management System empowered the client to optimize their inventory operations, improve data processing efficiency, and gain valuable insights for informed decision-making in a highly competitive market.

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