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Aerospace
Data Lake Architecture: Driving Efficiency and Innovation in Aerospace Production
Boeing centralized its CAD and PLM data using a data lake and reporting architecture built on Amazon Web Services (AWS). This solution streamlined data access, improved quality, and reduced costs through automation and cloud-based storage. Enhanced data analytics empowered Boeing to uncover valuable insights into product development, driving efficiency in design and manufacturing.
Date
April 15, 2024
Topic
Aerospace

Optimising Aerospace Innovation: Boeing's Data Transformation Journey

Context

Boeing, a leading global aerospace manufacturer, recognised the need to streamline its vast, fragmented Computer Aided Design (CAD) and Product Lifecycle Management (PLM) data systems to boost efficiency, enhance data quality, and reduce costs. With operations spanning 65 countries and a workforce of 150,000, the challenges of managing such diverse data streams were significant.

Challenge

The scattered nature of Boeing's CAD and PLM data across different systems and teams led to inefficiencies, hampering data access and quality. This fragmentation was costly, both in terms of maintenance and missed opportunities for data-driven insights.

Strategic Solution

In partnership with industry experts, Boeing initiated a comprehensive data centralisation strategy by constructing a robust data lake architecture on Amazon Web Services (AWS). This solution harnessed the power of AWS Glue for seamless data ingestion and transformation, ensuring data consistency and reliability across all platforms.

Implementation Highlights:

  • Data Lake Creation: Utilising AWS cloud technologies, including Amazon S3 for storage and Amazon Redshift for data warehousing, Boeing consolidated disparate data into a single, accessible repository.
  • Advanced Data Management: AWS Glue facilitated the automation of data extraction and processing, enhancing the integrity and usability of the information.
  • Scalable Reporting Architecture: Integration with advanced reporting tools like Tableau and QuickSight, underpinned by AWS Redshift, allowed for real-time data querying and analysis, optimized by a meticulously designed star schema for efficient data aggregation.

Outcomes:

  • Enhanced Data Quality: Centralisation substantially improved data accuracy across Boeing’s operations.
  • Accelerated Data Access: The new system reduced latency and optimised query performance, making critical data readily available.
  • Cost Efficiency: The cloud-based solution minimised reliance on physical infrastructure, significantly lowering maintenance costs.
  • Informed Decision-Making: With improved data analytics capabilities, Boeing gained deeper insights into its product development processes, enhancing design and production strategies.
Boeing's strategic overhaul of its CAD and PLM data systems transformed its approach to data management. The new centralized, cloud-based infrastructure not only reduced costs and operational complexities but also empowered Boeing to leverage data analytics for innovation and efficiency, setting a benchmark in aerospace technology management.