- Analytics & Modeling - Big Data Analytics
- Analytics & Modeling - Predictive Analytics
- Cement
- Product Research & Development
- Warehouse & Inventory Management
- Inventory Management
- Picking, Sorting & Positioning
- Cloud Planning, Design & Implementation Services
- Data Science Services
The client is a Fortune 500 industrial supply company that offers over 1.6 million quality in-stock products in categories such as safety, material handling, and metalworking. The company provides inventory management and technical support to more than 3 million customers in North America. Being a large-scale industrial supply company, it needed to efficiently manage large amounts of data, including data on inventory-related costs. The company was looking to extend its data warehouse solution, which collects data from multiple departments, and migrate it to the cloud to make it more scalable and cost-efficient.
The client, a Fortune 500 industrial supply company, was facing challenges with its existing on-premise data solution. The company needed to manage large amounts of data, including inventory-related costs, across multiple departments. The existing solution was causing significant overhead costs due to the hiring of on-site consultants for development and support. The company was looking to reduce these operational costs and migrate the solution to the cloud to make it more scalable and cost-efficient. To achieve this, they needed a reliable offshore development partner with extensive big data expertise.
N-iX, the chosen offshore development partner, developed a cloud-agnostic strategy for the client's cloud migration and built a unified data platform on AWS. The team built an AWS-based big data platform from scratch, extending and supporting the existing Teradata solution. A proof of concept was created to choose the data warehouse design and tech stack that fit the client’s business needs. The chosen solution, Snowflake, met the client’s approach of cloud neutrality, allowing easy scaling up and down of computing power for any number of workloads across any combination of clouds. The development process was designed to ensure that the client could easily change the cloud provider in the future. The use of Snowflake and Airflow technologies automated the data extraction process and minimized data duplication.
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