Manufacturing is not just evolving; it’s undergoing a revolutionary change, fueled by data and AI. 

Manufacturers are re-imagining their businesses to go beyond efficiently providing a unit of production (the next machine, vehicle or airplane) to also focus on creating technology-enabled businesses that are more scalable and resilient. The goal is to achieve higher growth through better end user experiences and stickier revenue streams.  

AI-driven technologies leveraging machine learning (ML) such as predictive maintenance, forecasting and inventory optimization — and more recently generative AI — are emerging as pivotal investments.

The challenge, however, lies in unifying the mountains of data collected from supply chain, production, product performance, sensors and customer feedback. 

One of those key data sources is SAP, a critical system of record at the heart of many manufacturing operations.

In order to achieve their AI ambitions, data leaders in manufacturing need to first achieve data readiness via centralizing their many varied disparate sources in a manner that is secure, efficient and governed — including SAP data. 

Unifying data unlocks AI and advanced analytics

In their current state, many organizations lack the data movement and access tooling to transition from measuring manufacturing reactively to predicting and prescribing action. 

Ensuring data is unified, accessible and governed is the foundation for these proactive projects — enabling a holistic view for supply chain optimization, quality control, customer support and more. 

For manufacturing organizations, that requires tackling SAP as a data source. They must navigate their own SAP application environment, complexity across cloud and on-prem environments, licensing requirements and an expansive data model with over 100,000 tables directly complicate data accessibility. 

The ripple effect means that manufacturing data professionals, as well as their stakeholders, often can't easily leverage critical ERP data to proactively predict equipment failures to prevent downtime, optimize inventory levels or personalize product offerings. 

How to move data from disparate data sources

The first step to unifying data involves getting data from all of your different sources, including SAP, into a unified data platform that brings the power of AI to your data and people.

Even if you have the resources available to build these pipelines initially, and the time required to do so, your engineers will spend outsized time on maintenance such as updating for APIs and fixing broken pipelines. 

Fivetran offers a robust and efficient solution with an extensive library of 500+ pre-built, fully-managed connectors allowing seamless and automated data replication. This also includes high volume, low-latency and low impact data replication from SAP. 

With features like Netweaver, Table Explorer and low-latency, log-based CDC replication, Fivetran can help you adhere to SAP licensing restrictions — while facilitating secure and efficient data movement. 

This empowers manufacturers to unlock the full potential of their operational data in SAP, unifying it with other existing data sources to:

• Enable a holistic view of supply chain optimization, quality control, customer support and more. 
• Predict equipment failures to prevent downtime
• Optimize inventory levels to personalize product offerings and best meet demand 

Choosing a next-generation data platform to unify SAP and non-SAP data  

Companies need a data platform that is tailor-made to address manufacturing’s most pressing needs while allowing the entire organization to use data and AI. 

The Databricks Data Intelligence Platform for Manufacturing is built on a lakehouse architecture and combines the industry's best data management, governance and sharing with the industry’s first built-in intelligence engine to democratize every person and process — supported with an ecosystem of manufacturing-specific Solution Accelerators and partners. 

The solution accelerators are developed for the most common and high-impact manufacturing use cases such as customer entity resolution, overall equipment effectiveness and predictive maintenance (IoT). They come with fully functional code and best practices that take you from idea to proof of concept (PoC) in as little as two weeks. 

This simplifies and unifies all of your data workloads key to manufacturing operations, including data processing, streaming analytics, business intelligence with SQL, machine learning and generative AI.

This will empower all of your data users, from data engineers, data scientists and business analysts. By integrating generative AI, Databricks democratizes data access to non-technical users with natural language interfaces, enabling data-driven decision making to enhance supply chain, production operations, field service and customer experiences

Manufacturers can take advantage of the full power of all their data and deliver powerful real-time decisions.

Leverage a modern data stack built for manufacturing 

The combination of Fivetran and Databricks equates to the critical pieces of a modern data stack. A modern data stack allows manufacturers to seamlessly move and harness all their data through a unified platform — reducing total cost of ownership and enabling AI at scale. 

This combination has helped global enterprises seamlessly integrate their SAP systems, enabling them to gain insights across their supply chain and manufacturing, resulting in improved efficiency, reduced downtime and increased productivity.  

Dive deeper into Databricks and Fivetran to start your journey towards becoming a data-forward, AI-empowered manufacturer today.

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