In their pursuit of digital transformation, automotive manufacturers are striving to optimize efficiency, improve customer experiences, drive revenue through innovation, and enhance risk management and regulatory compliance. Orion Governance’s Enterprise Information Intelligence Graph (EIIG), a self-defined data fabric, stands as a powerful catalyst in expediting this transformation in multiple ways.
Strengthening the COBIT Framework:
As automotive manufacturers adopt COBIT (Control Objectives for Information and Related Technologies), EIIG seamlessly embeds COBIT’s five principles within a comprehensive data governance context. This symbiotic integration of COBIT’s enterprise governance and EIIG’s data governance creates a harmonious synergy, enabling automakers to meet the dynamic demands of their business.
Breaking Down Data Silos:
Automotive manufacturers grapple with complex, siloed data landscapes, as a result of their intricate IT environment and diverse business ecosystem. Different divisions, departments, suppliers, and dealerships maintain their separate data systems. On the IT front, automakers tend to have deployed a wide range of technologies such as mainframes, AS/400, lakehouses, various ERP systems, ETL and reporting tools, and applications developed in Python or Java, likely in a multi-cloud environment. This complexity leads to a fragmented data environment and lack of a single source of truth, hampering digital transformation efforts. EIIG effectively overcomes these challenges by providing unparalleled coverage of diverse technologies. It automatically extracts metadata from over 70 technologies, constructing a unified knowledge graph that offers comprehensive insight into critical enterprise data. With EIIG, data silos are dismantled while data remains where it resides.
Unified Supply Chain Management Enhanced:
The automotive industry’s supply chain management encompasses a myriad of systems, from Enterprise Resource Planning (ERP) and Warehouse Management Systems (WMS) to Supplier Relationship Management (SRM) and Transportation Management Systems (TMS). These systems operate on diverse computing platforms. For example, still rely on mainframes for managing their ERP systems. Cloud platforms such as AWS and Azure may be used for analytics software.
EIIG’s comprehensive technology support enables automotive manufacturers to gain a holistic view of their entire supply chain data pipeline. This enhanced visibility allows for swift issue identification, leading to efficiency optimization and risk mitigation.
Digital transformation demands agile compliance with regulations such as GDPR, CCPA, and Sarbanes-Oxley. EIIG’s comprehensive technology coverage empowers automakers to fully understand their data, the initial step in meeting compliance requirements. Whether it’s data from mainframes, AS/400, SAP, Python, Java, or data visualization tools, EIIG offers end-to-end transparency. This traceability eliminates guesswork and provides auditors with clear compliance evidence. EIIG automatically maps compliance glossary terms with technical assets, and offers impact analysis directly in the lineage, simplifying compliance identification and risk minimization.
Regulations such as GDPR and CCPA require the identification of sensitive data like Personal Identifiable Information (PII) for data privacy protection. Since EIIG has established a centralized view of all data assets, automakers can visualize all PII data in one place and tag all of such data elements for compliance.
Trust in Reports:
EIIG propagates trust in reports by providing real-time data quality scores throughout the data journey. Using active metadata, EIIG enables organizations to visualize data quality scores throughout the data journey. It captures even the minutest changes and automatically sends lineage-based alerts to stakeholders so that they know how the reports will be impacted. They can trace the changes, identify their owners, and verify accuracy so as to be assured that the data they use for their reports is up to their quality and integrity standards. Such trust in reports is essential whether you are producing a financial report or a report for the auditors.
This level of trust is vital for cross-border data transfer. With the EIIG’s data visibility, automakers can easily tailor their reports to meet the requirements of different data protection laws and international data transfer agreements with total confidence.
Data Monetization and Consumer Trust:
EIIG facilitates data monetization while respecting privacy and consumer trust through automated data governance. It ensures data availability and access and facilitates collaboration through self-services while maintaining privacy rules, all without the need for human intervention.
Cost and Operational Optimization:
EIIG automates DataOps through tools like data lineage, data catalog, impact analysis, and active metadata. For example, automakers can identify duplicate data assets with EIIG’s Similarity Analysis, leading to significant cost savings. In addition, EIIG helps automakers make evidence-based decisions during their cloud migration journey, ensuring they understand their legacy data environment and multi-cloud reality.
EIIG offers clear visibility into cloud resource consumption and costs. It allows automakers to assign responsibility for cloud costs to various teams, fostering cost-conscious decision-making. EIIG’s impact analysis and similarity analysis further aid in cost optimization.
EIIG’s rapid deployment in weeks rather than months or even years ensures quick time-to-value, distinguishing it as a cost-effective solution for automakers.
In summary, Orion Governance’s EIIG is a self-defined data fabric that empowers automotive manufacturers in their digital transformation journey through its all-encompassing active metadata and data governance platform.
About the Author: Niu Bai, Ph.D. is the Head of Global Business Development at Orion Governance, Inc. Connect with Niu on LinkedIn.