A prominent manufacturing Organization was facing a lot of performance bottlenecks. There were multiple tools in use, such as SSRS, Power BI, Tableau for reporting and KNIME, Snaplogic for ETL, discreet databases and other technologies to manage. This was adding a lot of overhead cost and the true potential of data could not be unlocked for Machine learning and advanced capabilities.

• Data Silos and Integration Issues: The organization was relying on multiple disparate tools and databases. This created data silos, where information is fragmented and difficult to access and integrate. This fragmented data landscape hindered the ability to gain a holistic view of operations and limits the potential for advanced analytics and machine learning.
• Increased Operational Costs and Inefficiency: Managing a complex ecosystem of tools required significant resources and ongoing maintenance. The duplication of effort across various platforms led to inefficiency and drove up operational costs.
• Limited Access to Data for Advanced Analytics: The siloed nature of the data and the reliance on disparate tools made it difficult to prepare and access data for advanced analytics and machine learning. This restricted the organization from unlocking the true potential of its data for predictive insights and process optimization.

Airo provided a comprehensive Data for AI solution designed to address these challenges and modernize the manufacturing company’s data platform:

• Airo’s Data team conducted a quick assessment and prepare the plan for data migration.
• Full-Fledged Migration involved Data warehouse, Reports, Ingestion Pipeline along with users and security/ scheduling control to a more robust cloud-based solution having Datalake and Deltalake with Synapse Analytics and Databricks.
• We converted all Pipelines to ingest data directly in a new solution.
• We migrate one time data from existing Warehouse to the new platform and changed reports connection for faster turnaround.
• We consolidated multiple reporting tools into Power BI with data model consolidation
• Pipelines were reduced by using metadata injection increasing maintainability and reusable Databricks notebooks.
• We also set up governance and quality processes.

The implementation of Airo’s Data for AI solutions led to significant improvements and benefits for the manufacturing company:

• Effortless Scalability: Our solution effortlessly scaled to accommodate 3x data growth without compromising performance. This translated to reduced maintenance costs and freed up IT resources to focus on strategic initiatives.
• Deeper Insights with AI/ML: We’ve integrated advanced AI/ML features to unlock powerful insights from customer data. This empowered customer to make data-driven decisions and optimize operations like never before. For instance, AI-powered anomaly detection led to a 15% reduction in production line downtime.
• Data Governance Reinvented: Improved data governance practices ensured the accuracy, security, and accessibility of customer data. This translated to increased trust in data-driven decisions and led to a 20% improvement in operational efficiency through better resource allocation and process optimization.

Struggling with siloed data and disparate tools, the manufacturer lacked a unified data platform for advanced analytics. Airo’s Data for AI solution consolidated data, implemented robust cloud-based technologies, and streamlined processes. This resulted in effortless scalability, with the infrastructure accommodating 3x data growth. Additionally, AI/ML integration led to a potential 15% reduction in downtime, and improved data governance practices yielded a possible 20% boost in operational efficiency. This transformation empowers the manufacturer to make data-driven decisions and optimize operations for a competitive edge..