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In the semiconductor industry, research and development tasks, manufacturing processes, and enterprise planning systems produce an array of data artifacts that can be fused to create an intelligent semiconductor enterprise. Through intelligent data use, an intelligent semiconductor enterprise accelerates time to market, increases manufacturing yield, and enhances product reliability.

The Databricks Intelligence Platform suits semiconductor enterprises’ unique needs for performance, collaboration, and self-service access. Built on a lakehouse architecture with leading technologies of Delta Lake, Apache Spark™, MLflow, Mosaic AI, and Unity Catalog, the Data Intelligence Platform is the substrate for semiconductor companies to connect engineering technology (ET), operational technology (OT), and information technology (IT) data.

The Enterprise Data Substrate for Semiconductors

The Databricks Data Intelligence Platform connects all data systems across the semiconductor, computer, and electronics value chain.
The Databricks Data Intelligence Platform connects all data systems across the semiconductor, computer, and electronics value chain.

The substrate connecting engineering, manufacturing, and sales is the enterprise data platform. The Databricks Intelligence Platform addresses each of the four V’s of data present in semiconductor company requirements:

  • Variety: The substrate must support a variety of data, from simulation results to time series sensor data and quality assurance images. Databricks has built-in keyword bindings for all of the data formats natively supported by Apache Spark and supports extensions in Python and Java for proprietary formats such as Standard Test Data Format (STDF).
  • Velocity: The substrate must support slow-moving enterprise transactions, recurring engineering simulations and field crash logs, and high-frequency manufacturing sensor data. Databricks’ Delta Live Tables and Photon engine allow you to easily use a single copy of data for both batch and streaming operations and provide incremental processing at scale.
  • Volume: The substrate must support extremely large data volumes due to the high-fidelity nature of engineering simulations and process control datasets. Databricks sits on top of nearly infinitely scalable cloud object storage and can directly read compressed files in many file formats.
  • Veracity: The substrate must support data integrity and governance to protect core intellectual property while making data accessible to various department stakeholders. Databricks’ Unity Catalog provides centralized access control, auditing, lineage, and data discovery capabilities.

On top of the substrate, intricate data-driven models can be built to feed the intelligent semiconductor enterprise. Databricks Mosaic AI provides unified tooling to build, deploy, and monitor AI and ML solutions — from building predictive models to the latest GenAI and large language models (LLMs). Mosaic AI enables semiconductor companies to securely and cost-effectively integrate their enterprise data into the AI lifecycle that powers digital twins and autonomous agents.

Conducting an Integrated Intelligent Ecosystem

Much like the components on a printed circuit board (PCB) work together to form a complete system, the Databricks Intelligence platform connects the data generated by all enterprise data systems within an open data lake. For example, enterprise resource planning (ERP) can be connected with recipe (RCMS), and transportation (TMS) data to provide cradle-to-grave visibility of carbon footprint.

Databricks unifies the data and governance of all semiconductor data systems on top of an open data lake.
Databricks unifies the data and governance of all semiconductor data systems on top of an open data lake. An open data lake refers to a data lake in which data is stored in an open format, like Delta Lake, so users avoid lock-in to a proprietary system.

The imperative for semiconductor companies to harness the full potential of their data is clear. When the velocity, variety, volume, and veracity of the data substrate are managed effectively, the enterprise accelerates time to market, improves manufacturing yields, and boosts product reliability. Through data-driven models and simulations evolving from predictive to autonomous, efficiencies are created that impact every facet of the semiconductor value chain.

Ultimately, the integration of Databricks’ Intelligence Platform into semiconductor enterprises is not just about managing data—it's about transforming it into a strategic asset that propels innovation and strengthens operational excellence while maintaining strong governance. Leading semiconductor companies like Intel, AMD, NVIDIA, and ASML are modernizing their enterprise data and AI efforts using Databricks in the cloud. Connect with your Databricks representative today to discover how we meet your unique challenges and propel your company into an intelligent enterprise.

To learn more, visit our Manufacturing solution page.

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