Our client, a global telecom major embarked on two key initiatives of transforming their solutions and replacing the legacy systems for supplier intelligence and big data management. In specific, the client wanted to achieve a 360-degree view of spend across all suppliers for each of their equipment and migrate business intelligence infrastructure to cloud-based big data infrastructure.
Resolve Tech team consisting of architects, and specialist engineers with deep expertise & experience in data engineering, big data, and data analytics have worked along with the client team in implementing new technologies for supplier intelligence and big data infrastructure. Best-fit technology stack was chosen for all the layers across the data life cycle from capture to ingesting, storage, and analytics. The team designed and implemented several solutions across the data life cycle so that all activities of all suppliers are tracked across the journey. In parallel, migrated the legacy supply chain business intelligence data & infrastructure to AWS-based scalable cloud stack. With the successful implementation of the solutions, the client was able to gain deeper insights into supplier activities and spend analytics there by realizing significant savings on supplier spend and data infrastructure.
Instituted a comprehensive data life cycle from capturing data (client’s public channels and specific applications) to ingesting the data into target infrastructure and processing & storing the data in a form that helps real-time and operational reporting & analytics
Designed and implemented AWS Cloud Solution & Architecture for storing & managing big data at organization level and for dynamic scaling based on business growth.
Designed and implemented highly scalable data stores & pipelines leveraging open-source technologies and streamlined data pipelines that are highly optimized for large data sets thus ensuring high-throughput and low-latency operations.
Selected and implemented right technologies based on the client requirements and the data life cycle specific functionality – Kafka, Apache Sqoop for Data Ingestion; Apache Spark, AWS tools for Data Processing; Amazon S3, RDS, Apache Hive & HBase for Data Stores; Tableau, Qlik Sense for Data Analysis & Visualization.
Implemented Big Data Infrastructure on Hortonworks Data Platform (HDP) that provides distributed storage and helps in processing large, multi-source data sets
Leveraged advanced Tableau functionality to create visually rich analytical & impactful dashboards helping users to easily explore a variety of data sets and conduct deeper business analysis