Canada
Puerto Rico
USA
Belgium
France
UK
India
Client Background
The client is a Swedish furniture giant located across Europe.
Client Need
The client faced rapidly increasing data storage costs due to the high licensing fees associated with their SAS database, hindering other strategic initiatives. Other challenges include:
Experienced performance bottlenecks and delays in data analysis due to the limitations of their SAS database in handling complex mathematical operations
Inability to process unstructured data created data silos and delayed efficient data utilization
Solution
We implemented the following solutions:
Reduced Data Storage Costs: Implemented an open-source framework (Hadoop distribution HDP2.4) for big data storage and processing
Improved Data Analysis Performance: Migrated to the Hadoop ecosystem, enhancing query performance and accelerating data analysis
Simplified Data Management: Facilitated upfront business logic by creating a data lake, providing a centralized and accessible repository for data
Data Integration: Executed an ETL process to extract data from source systems and load it into a data warehouse
Realized Benefits
The client derived the following benefits:
Boosted scalability by automating fault-tolerant production, ensuring continuous operations, and minimizing downtime
Achieved significant cost reduction through high-volume batch processing, resulting in lowered hardware costs and faster performance
Accelerated data retrieval by pulling pre-aggregated datasets into the SAS database, enabling faster querying
Tools & Technologies
Hadoop
SAS
Microsoft Active Directory
Apache Ambari
Oozie
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