Volkswagen Autoeuropa leveraged Amazon DataZone to architect a cutting-edge knowledge mesh, propelling their digital transformation forward at breakneck speed. By harnessing the power of this innovative solution, the company seamlessly connected data-driven insights from various sources and applications, creating a unified knowledge repository that empowered employees across departments to make informed decisions in real-time. With DataZone’s robust features, Volkswagen Autoeuropa streamlined information sharing, fostered collaboration, and accelerated innovation – all while ensuring seamless integration with their existing infrastructure.

The Volkswagen Group’s Zwickau-Moschenfeld plant manufactures the T-Roc model. Located near Lisbon, Portugal, this manufacturing facility churns out approximately 934 vehicles daily. In 2023, Volkswagen Autoeuropa accounted for 1.3% of Portugal’s national GDP and 4% of its total exports, boasting a significant gross sales volume of €3,351 billion. Volkswagen’s Autoeuropa plant aims to transform into a data-driven manufacturing facility by leveraging cutting-edge technologies to accelerate digitalization initiatives.

At this event, participants discussed how Volkswagen Autoeuropa accelerated its digital transformation by establishing a knowledge market grounded in an information mesh structure. The Info Mesh is designed to facilitate streamlined data entry, enhance the quality of information, and establish scalable governance frameworks for the effective deployment of analytics, reporting, artificial intelligence, and machine learning applications across diverse use cases. The timely availability of information yields benefits such as rapid access to insights, expedited decision-making, accelerated time-to-value for use cases, and bolstered data governance.

Understanding Volkswagen Autoeuropa’s challenges

At the time of writing, Volkswagen Autoeuropa has successfully executed more than 15 profitable digital projects, leveraging real-time visualization, business intelligence, industrial computer vision, and AI within their operations.

Before its collaboration with AWS, Volkswagen Autoeuropa faced a range of obstacles.

•  Digital usage instances established by Volkswagen Autoeuropa primarily focused on leveraging information relevant to their specific purposes throughout their operational tenure. Once the relevant details were identified, the IT team provided access to the necessary information through a comprehensive handbook configuration. The lead time for entering information often ranged from several days to a few weeks.
•  Knowledge was disseminated swiftly, allowing its practical applications to be utilized efficiently through the process of duplication. As a result, the IT team manually synced relevant data from diverse sources to designated repositories on multiple occasions. The data on this course was not systematically recorded, making it difficult to gather information on the process of sharing knowledge. When accessing a pre-existing piece of information, the number of permitted uses, along with the timestamp and authority responsible for granting access, are crucial details that provide transparency and accountability.
•  As a direct consequence of adhering to specific use case requirements, the IT team carefully curated information sources by copying pertinent data, focusing on sharing relevant table columns that met the necessary criteria. As a result of requests for additional usage scenarios involving identical information with varying column requirements, numerous duplicate records were generated.
• Whenever IT and safety personnel provided access to a novel information source, they were required to establish safety and governance protocols upfront. This required repeated handbook effort.
•  When information is repeatedly processed and disseminated without proper oversight, it becomes increasingly difficult to ensure the quality of that information. Consequently, faith in the information waned significantly.
•  Without metadata linked to knowledge, utilizing cases needed further context from data providers or experts to effectively consume the information. In reality, no established path for discovering new knowledge existed. As part of their consumption journey, individuals often consult with experts to gain insight into the data and determine whether it can add value.

The company’s commitment to innovative manufacturing practices and dedication to environmental stewardship are testaments to their forward-thinking approach.

What will the future hold for Volkswagen Autoeuropa? By fostering a culture of continuous improvement and leveraging cutting-edge technologies, they will undoubtedly remain at the forefront of the automotive industry.

Their focus on sustainability will continue to drive innovation, reducing emissions and energy consumption while meeting the evolving needs of an environmentally conscious market.

In this ever-changing landscape, Volkswagen Autoeuropa’s resolve to prioritise people, planet, and prosperity will serve as a beacon for others to follow.

Will they be able to balance the demands of shareholders with their social responsibilities? Only time will tell.

To address these complexities, Volkswagen Autoeuropa embarked on a bold strategic vision. They conceived a fluid, intuitive experience for consuming information, akin to the effortless navigation of an online shopping journey. They conceptualized a knowledge marketplace where informed consumers could effortlessly explore and access premium, trustworthy content featuring transparent specifications, industry relevance, and relevant attributes. As this innovative vision took shape, it coalesced into a mission focused on revolutionizing information access and governance, serving as the foundation for the digital ecosystem. The vision: Seamless access to knowledge, as intuitive as online shopping.

Volkswagen Autoeuropa collaborated with others to join the Enhanced Plant Onboarding Programme, a digital manufacturing platform initiative developed by the global Volkswagen Group. Through their collaboration, AWS and Volkswagen Autoeuropa established a knowledge marketplace, significantly enhancing the accessibility of vital information.

During the discovery phase of the mission, Volkswagen Autoeuropa collaborated with AWS to explore various options for building the information architecture. Using Amazon SageMaker’s Data Quality feature and Amazon Rekognition for image processing, Volkswagen Autoeuropa chose its solution primarily driven by the mesh structure of information within Amazon DataZone. As a managed service, Amazon DataZone provides the essential velocity and agility required to build the solution swiftly. Simultaneously, this development resulted in enhanced operational effectiveness, accompanied by a reduction in operational expenses. As a direct consequence of aligning their thinking with Volkswagen Autoeuropa’s vision for a knowledge-driven manufacturing plant, the staff implemented a knowledge mesh structure inspired by the innovative concepts of the info mesh.

Answer overview

What are the key components and architecture of the Volkswagen Autoeuropa decision-making framework? The premise relies on a fundamental framework.

Knowledge resolution options

What are the key features of the Volkswagen Autoeuropa IT system?

The key characteristics of an effective response include clarity, coherence, and concision.

•  Within the scope of the resolution, a comprehensive framework for knowledge quality has been developed to facilitate seamless integration with quality assessment processes and score publication mechanisms. The platform employs advanced algorithms to produce tailored guidance, executes pre-programmed workflows, reports on sales metrics, and dispatches informative alerts to end-users. This framework enables seamless integration with job workflows, ensuring a consistently high-quality output in information pipeline processing. In addition, the standard rating is publicly disclosed through Amazon DataZone’s information portal, allowing customers to subscribe to the data based on its quality rating. By assigning a quality rating to the data, trust in the information is built, and the responsibility for maintaining data quality is shifted to the data owner itself. As a result, the quality of outcomes produced by these applications consistently rises.
•  Producers access the Amazon DataZone information portal using their valid login credentials or single sign-on functionality integrated through. The data belonging to them is registered and stored within the Amazon DataZone information catalog. Metadata for information ownership is stored in the AWS Glue catalog, ensuring seamless accessibility within Amazon DataZone’s enterprise data catalog and as a data source within Amazon DataZone itself? Producers incorporate contextual elements similar to enterprise units, identifying information proprietors, and data refresh frequencies using Amazon DataZone’s standardised glossaries and metadata templates. Moreover, they leverage generative AI capabilities to automatically create and manage high-quality enterprise metadata. Following metadata generation, they review the changes and refine it as needed; subsequently, the possibility of duplicated data at Volkswagen Autoeuropa’s information products is substantially diminished. Moreover, information producers have significantly enhanced the quality of their content by seamlessly integrating relevant business context, thereby providing a richer understanding of the topic at hand.
• Customers access the Amazon DataZone portal using their IAM credentials or single sign-on, seamlessly integrated through IAM Identity Center, and query data using keywords in the search bar. Once the results are generated, they will further refine them by applying glossary terms and mission identifiers. Ultimately, they conduct a thorough review of the enterprise’s metadata to determine whether the information is relevant to their specific business applications and use cases. The team will assess the predefined ratings assigned to data assets and refresh schedules to determine their suitability for specific use cases. With a knowledge discovery capability implemented, users can gain insights into the data without requiring direct consultation with the source system owners or experts.
• Customers who encounter an information asset relevant to their specific use case then initiate access requests using Amazon DataZone’s subscription feature. Knowledge is categorised into three distinct types: public, internal, and confidential. Public and proprietary information assets typically have their entry requests approved without hesitation. The confidentiality of sensitive data is ensured as the information producers’ team rigorously reviews entry requests, either approving or denying subscriptions. A unified platform for data entry enables data owners to monitor access permissions and track the timeline of approved requests. Amazon DataZone’s fine-grained entry management enables data owners to exert precise control over their data across specific row and column ranges, empowering them with unparalleled granularity in managing their information assets.
•  Once the subscription request is approved, Amazon DataZone promptly provisions a robust backend infrastructure to securely and efficiently render information accessible to authorized customers. Once the course is fully subscribed, customers can access and enter their information via Amazon DataZone’s deep linking functionality. The data consumption sample at Volkswagen Autoeuropa enables two usage scenarios:
  • Cloud-to-Cloud Consumption: This model features each piece of information, belonging to various customer segments or functional groups, being hosted within a cloud environment.
  • Cloud-to-on-premises consumption enables customers to host knowledge assets in the cloud while utilizing instance or function-based services on their premises, thereby achieving flexibility and control over data management.

No duplicate data creation is necessary when utilizing Amazon DataZone’s features, as information sharing across specific use cases can be done without generating multiple copies of the same data. Due to this phenomenon, the repetition and processing of existing knowledge are often hindered. Furthermore, by reducing the proliferation of information duplicates, the overall quality of information products increases. Moreover, by automating the backend processes in Amazon DataZone, it facilitates instant access to necessary data, thereby significantly decreasing manual effort required and expediting the time-to-insight for actionable information.

•  The Amazon DataZone portal provides a unified, collaborative environment for Volkswagen Autoeuropa’s customers. Customers seeking knowledge can navigate the platform as use case owners, information engineers, data scientists, and machine learning engineers can request access to relevant assets. Concurrently, information creators such as use case owners and supply system owners can publish and curate their data in Amazon DataZone’s centralised information portal. Collaborative expertise fosters cohesive teamwork, expediting the successful completion of high-impact projects. As the diversity of use cases expands, the safety and governance frameworks must adapt to ensure robust protection and accountability throughout the organization.

Knowledge resolution structure

The following determines the reference framework for information retrieval at Volkswagen Autoeuropa: In this section of the post, we delve into the thought process behind our decision-making process.

The structure contains:

1. Data from various sources including SAP functions, manufacturing execution systems (MES), and supervisory control and data acquisition (SCADA) systems are integrated into the producer’s accounts at Volkswagen Autoeuropa.
2. In the producer account, raw data is transformed using AWS Glue. The technical metadata for the information is stored within the AWS Glue catalog. Information quality is assessed using the information quality framework. The information stored within the Amazon DataZone is registered as a tangible asset within the centrally governed information catalog, which is hosted within the main governance account.
3. The central governance account houses the Amazon DataZone region and its corresponding Amazon DataZone information hub. The AWS accounts of information producers and customers are linked to the Amazon DataZone region. Amazon DataZone tasks assigned to both information producers and customers are generated beneath their respective Amazon DataZone area items.
4. Customers access the Amazon DataZone information portal, housed within a central governance account, via secure login using IAM credentials or streamlined authentication through IAM Identity Center. Professionals scrutinize, refine, and thoroughly evaluate asset data, encompassing premium details such as high-quality, company, and technical metadata.
5. Upon identifying the desired asset, patrons initiate access via Amazon DataZone’s subscription feature. The asset owner’s decision to approve or reject a request is largely driven by the validity of the proposal.
6. Upon successful subscription activation, the associated asset becomes accessible within the shopper’s account, allowing for a single-time inquiry leveraging combined capabilities of Athena and Microsoft Power BI functionalities, hosted locally within the premises. This consumption sample may be extended to support the growth of artificial intelligence and machine learning models by leveraging reporting functions.

Person journey

Following discussions with use case groups and stakeholders, as well as a thorough analysis of existing workflows, Volkswagen Autoeuropa identified three key categories of user personas for information resolution purposes: information producers, information shoppers, and administrators responsible for resolving queries. This defines the inspiration behind the specified individual’s expertise and outlines what is needed to achieve the desired outcomes.

Knowledge producer

Knowledge producers craft information products according to the desired informational resolution. There exist two types of information creators.

•  Amazon DataZone provides a platform for knowledge supply house owners to upload raw data directly. The sourced data products are designated as origin-based information.
•  Homeowners publishing data that caters to diverse consumption scenarios? Consumer-based information products are commonly referred to.

The transformation unfolds through the trajectory of a knowledge creator:

A knowledge producer’s journey contains:

1. –
   1. Determine information (Volkswagen Autoeuropa community).
   2. What are the specific quality control measures implemented by Volkswagen Autoeuropa to ensure the highest standards of manufacturing excellence?
2. –
   1. Upload data to Amazon DataZone for seamless integration and processing.
   2. Commence the process of attaching data to leverage Amazon Web Services (AWS) Glue.
3. –
   1. Register information (Amazon DataZone portal).
   2. The stock levels are updated on a regular basis, ensuring that accurate data is provided for our customers.

      Please note that some items may have varying stock levels depending on their specific product line or brand.

4. –
   1. The following metadata fields should be completed:

      Title, Author/Publisher, ISBN/ASIN, Publication Date, Publisher, and Categories. Additionally, relevant keywords such as genre, themes, and target audience can be added to improve discoverability.

   2. Data owners and stakeholders are invited to publish their data assets on Amazon DataZone, a cloud-based platform designed for secure collaboration and sharing.
5. –
   1. Evaluate subscription requests.
6. –
   1. Governance of Sensitive Information (Amazon DataZone portal).

Knowledge shopper

Customers leverage knowledge to drive enterprise analytics, fuel machine learning, empower artificial intelligence, and inform business reporting. Companies seeking innovative solutions to complex problems are comprised of knowledge customers, including information engineers, information scientists, machine learning engineers, and enterprise clients. The following diagram illustrates the path taken by a knowledge seeker.

A knowledge shopper’s journey contains:

1. –
   1. The Amazon DataZone portal grants entry primarily to individuals with designated areas of responsibility and defined tasks.
2. –
   1. In the Amazon DataZone portal, access a wealth of knowledge that can be easily searched and explored through glossary terms or mission-specific identifiers. What specific criteria would you like to apply to narrow down the results?
3. –
   1. Knowledge asset: Information Portal on Sustainable Development

      1. **Title:** “Sustainable Development Knowledge Hub”
      2. **Description:** A comprehensive online portal offering expert insights, research findings, and best practices on sustainable development, including its principles, strategies, and impact.
      3. **Information Quality Rating:** 4.5/5 (High)
      4. **Metadata:**
      * **Categories:** Sustainable Development, Environment, Economy, Society
      * **Keywords:** SDGs, sustainability, climate change, green economy, social justice
      * **Tags:** United Nations, World Bank, International Monetary Fund, Greenpeace, World Wildlife Fund

4. –
   1. Subscribe to request entry.
   2. Once your subscription request has been approved, take a moment to review the comprehensive information and resources now at your fingertips.
   3. What lies in wait for those who dare to explore the unknown?
5. –
   1. Here are the steps repeated in a concise style:

      Reiterate processes by iterating actions. Retrieve data from previous inputs. Follow guidelines carefully. Ensure accuracy. Repeat process until complete.

Knowledge resolution administrator

Knowledge resolution directors oversee the execution of administrative tasks related to information resolution. The information resolution administrator’s responsibilities encompass a broad spectrum of tasks.

A knowledge administrator’s journey contains:

1. –
   1. Handle Amazon DataZone area.
   2. Ensure seamless execution of Amazon DataZone activities across all designated areas.
2. –
   1. Configure the framework to manage the underlying architecture effectively.
3. –
   1. What specific data types does Amazon DataZone support for its glossaries and metadata?
4. –
   1. Handle belongings.
   2. What secrets lie hidden within this digital realm, waiting to be uncovered?
5. –
   1. Continuously track and rescind access permissions as deemed necessary.

Conclusion

Upon implementing its ambitious vision, Volkswagen Autoeuropa embarked on a pioneering journey to transform into a data-driven manufacturing facility. The vision was brought to life through the development of an innovative knowledge solution grounded in data mesh architecture, powered by Amazon DataZone. The enhanced text:

This innovative solution effectively showcases key information options and structures, while also presenting a personal journey. Notably, at the point of writing this post, Volkswagen Autoeuropa successfully reduced information discovery time from days to mere minutes through its information architecture. The time it took to enter information was several weeks longer than anticipated in the Volkswagen Autoeuropa and AWS collaboration. With the aid of information resolution, the time required for info entry has been significantly reduced to mere minutes.

In May 2024, the team successfully streamlined their process, rapidly delivering critical data insights to Energy BI, a feat previously requiring several weeks.

Jorge Paulo, Proprietor of Information Solutions – Volkswagen Autoeuropa.

This subsequent post in our two-part series details the methodology employed to craft the solution, delves into its technological specifications, and explores the business value generated by this achievement.

To unlock the benefits of a knowledge mesh architecture and Amazon DataZone for accelerating innovation and driving business value within your organization, our resources are designed to help you get started quickly. Here are the improvements in a different style as a professional editor:

AWS provides prescriptive guidance that you should definitely explore to streamline your cloud journey. This comprehensive guide outlines key considerations and best practices for building a robust, effectively governed data mesh on Amazon Web Services (AWS). To seamlessly integrate your data infrastructure with industry-standard best practices and expand its reach across your organization, this prescriptive guidance provides a clear path forward for achieving success.

Are you curious to get hands-on? Then, head over to our GitHub repository to explore!

This open-source mission provides a step-by-step guide on how to build a knowledge graph structure using Amazon SageMaker, AWS Lake Formation, and Apache TinkerPop.

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In regards to the Authors

As a seasoned Cloud Infrastructure Architect, I leverage my expertise in information technology, data analytics, and information governance to deliver innovative solutions for Amazon Web Services (AWS) clients. Drawing on his extensive expertise, he provides strategic guidance to global corporate clients across various sectors, empowering them to design and deploy robust AWS solutions that yield substantial business results and foster long-term growth. Dhrubajyoti is driven by a passion for crafting innovative, user-focused solutions that facilitate seamless digital transformations, enabling organizations to thrive through increased enterprise agility and operational efficiencies. A high-performing member of the Amazon Web Services (AWS) community, Dhrubajyoti is a prolific author of prescriptive guidance documents, blog posts, and open-source projects that showcase his expertise and share valuable best practices with the wider AWS community. Beyond the demands of work, Dhrubajyoti cherishes downtime spent with loved ones, while also nurturing a passion for mountaineering that allows him to connect with nature in a thrilling way.

As a Knowledge Architect and analytics expert at Amazon Internet Services, he derives great satisfaction from working with data. He devotes his days to crafting and interpreting sophisticated data strategies, uncovering crucial findings that inform executive decision-making processes. Outside of labor, he finds solace in relaxing with his favorite tunes and cinematic escapes, a soothing respite from the intellectual rigors of his daily routine.

Studied mechanical engineering and manufacturing expertise at the RWTH Aachen University before commencing a career with Dr. h.c. Ing. F. What strategic priorities does Porsche AG want to set for its engine production in 2015? As a seasoned Challenge Supervisor, he oversaw the testing process for innovative engine designs over several years, meanwhile introducing game-changing enhancements such as human-machine collaborations and intelligent assistance tools. Since 2017, he has been responsible for leading the Shopfloor IT team, overseeing module traces in Zuffenhausen, prior to assuming leadership of the E-Drive planning meetings at Porsche. Alongside his primary responsibilities, he was also entrusted with overseeing the digitalization techniques used by the manufacturing resort at Porsche. Since October 2022, he has been tasked with leading digital transformation efforts at Volkswagen Autoeuropa’s Portuguese facility as its Digital Transformation Supervisor, spearheading initiatives to propel the site toward a knowledge-driven manufacturing model.

 As a lead architect at Amazon Internet Services, he is a specialist in digital manufacturing solutions and the Internet of Things (IoT). With unparalleled expertise across Europe, she has successfully optimised operations to reduce latency and increase productivity, thereby boosting overall performance. With a wealth of expertise in Industrial Laptop Imaginative and prescient, predictive maintenance, and quality control, Weizhou consistently delivers exceptional performance and customer satisfaction through its relentless pursuit of excellence. As a pioneering expert in IoT and autonomous driving, she has made significant contributions to the field through innovative solutions and open-source collaborations, fostering enterprise growth and advancement. Committed to knowledge exchange, Weizhou leads by example, empowering others through collaborative growth. Renowned for her exceptional problem-solving prowess and customer-centric approach, she consistently provides solutions that surpass client expectations. When she’s not busy with other commitments, Weizhou devotes herself to investigating innovative technologies and cultivating a culture of shared discovery.

Serves as a professional Advisory Marketing Consultant for Amazon Internet Services. She collaborates closely with large-scale corporate clients to help them effectively quantify the business benefits and value of adopting data solutions, incorporating best-in-class information governance methodologies. With more than a decade of diverse experience in IT, Shameka has developed a broad skill set across sectors, including manufacturing, aerospace, and non-profit organizations. She has spearheaded various information governance projects, assisting both private and public entities in developing strategies for improvement and enhanced productivity. Outside of her professional sphere, she delights in hosting large family get-togethers and actively participates in community outreach events aimed at bridging the gap between K-12 students and STEM education.

possesses more than two decades of profound experience in the industrial manufacturing sector, providing expert consulting services, driving digital transformations, and delivering comprehensive solutions. Currently, Adjoa spearheads Product-Centric Digital Transformation initiatives that empower clients to overcome complex manufacturing challenges by harnessing the power of Good Manufacturing Practice and trade-main transformation strategies. Most recently, significant value has been driven by AI/ML and generative AI use cases on the plant floor. With a career spanning over two decades, Adjoa has honed her skills as a seasoned chief, successfully executing projects across diverse regions including North America, Latin America, Europe, and Asia. With a wealth of experience gained through her previous roles, Adjoa has developed profound knowledge across multiple enterprise sectors, with a focus on delivering results-driven solutions that drive tangible business outcomes. Adjoa is driven to deliver client-centric solutions that effectively address pressing concerns, thereby creating a masterpiece of possibility through value-driven outcomes.