Industrial Data Summit has an interactive format that enables in-depth peer-to-peer discussions around your key business challenges, providing real insight and value.
This includes a combination of plenary (keynotes, 5-minute idea, and a panel discussion) and our ‘deep-dive’ roundtable discussion breakout sessions, which are limited to 5 to 8 delegates in each session.
Share your ideas, opinions, and experiences in a collaborative and inclusive environment. Learn from others’ experiences and expertise and gain insights and knowledge from your peers who have faced similar challenges and overcome them.
Plenary
Our Plenary sessions bring together all delegates in a single room – concentrating the event’s focus on to a series of high-profile content sessions. These content sessions include case studies delivered by our keynote speakers as well as expertly moderated panel debates.
Discussion Tables
Select the topics that matter most to you! Over the course of the Summit, three rounds of Discussion Sessions will take place. You will have the opportunity to choose between eight Discussion Tables for a 60-minute interactive Q&A, hosted by a world-class manufacturer and a technology expert. The selection of topics will cover Data Management and Data Insights.
Welcome speech from our Chair.
The manufacturing sector is the latest domain to embrace the digital and data transformation ethos. Whilst there ground to make up, there’s also huge opportunity to accelerate change by learning from successes and failures in other sectors.
- This talk will highlight the investments and change initiatives necessary to grow and thrive in the fourth industrial revolution and beyond using examples from leading change in the public and private sector.
We know it’s the right thing to do, we know how powerful data can be, so why is it so challenging to create a data driven culture? There is a tendency to delve into the technicalities of digital transformations, to focus on the latest technology and how it can be implemented. But without the right foundations and organisational culture no amount of new tech is going to create a data driven culture.
- The challenges
- Laying the foundations
- Creating a digital culture
Accelerating Digital Transformation in Manufacturing with Connected Data
The UK manufacturing industry faces challenges in collecting and integrating data from multiple sources to make informed business decisions amidst Industry 4.0. To streamline operations and drive growth, companies need to optimise the power of data.
This roundtable will discuss the following:
- Strategies to overcome data silos across legacy systems and new technologies to support business organisations and processes.
- How to optimise data use and build a connected data infrastructure with data integration, management, and governance.
- How to create a data culture to support business processes, incentivise data sharing, and enhance employee and customer experience while generating new revenue streams.
A data strategy is not a one-and-done. Data strategies evolve. From an initial focus on getting your data house in order (efficiently storing and effectively protecting data) to a plan enabling its use, a data strategy becomes a roadmap for delivering business value.
Come join Snowflake to discuss the elements of a data strategy, with a focus on effective data governance that facilitates the use of data to deliver differentiation and competitive advantage. As Thomas Edison says, “The value of an idea lies in the use of it.” The same goes for data.
Join Snowflake and your peers to:
- Learn how other companies define and refine their data strategy
- Discuss how data governance allows you to know, protect and unlock the value of data
- Explore how data ecosystems expand data collaboration internally and externally
How data governance is transforming shop floor operations in manufacturing.
Increasing numbers of manufacturers are transitioning their operations to cloud-based platforms to realize benefits including cost savings, convenient access to manufacturing data for enterprise personnel, improved data analysis and insights, and scalability.
However, with the migration of manufacturing data to the cloud, challenges have emerged, including the management of large volumes of data. When transitioning to cloud-based platforms, data governance and security play crucial roles.
- What are the challenges associated to managing all this new information?
- Why is manufacturing data being moved / copied to the cloud?
- How are data governance and security instrumental while moving to cloud?
Legacy infrastructure and applications like Historian servers and SPC (statistical process control) systems hold many back when it comes to modernization and reducing costs. Cloud IOT services have dramatically changed this, but what exactly should be leveraged and how. Join Storm Reply in this session to discuss:
- What should or should not live on Amazon Web Services (AWS) when it comes to machine data
- Are edge analytics with AWS IOT services actually useful
- Is computer vision and digital twin complex and costly
Data is a critical component as it allows for the integration of systems and the ability to make informed decisions that improve efficiency and safety.
Applications and best practice
Data collaboration, robust analytics, treating data an as asset.
Cost reduction, revenue growth, data sharing
Future outcomes for process optimization, supply chain and maintenance.
Using Digital Twins to virtually monitor and manage assets performance and manufacturing operations.
Implementing robust data protection strategies to better secure you data and meet regulatory compliance requirements.
Whether you’re a data manager, analyst, or another kind of data leader, enabling the organisation to make the best possible use of assets is now crucial to business success.
Delegates choose from the same 12 topics for their third and final discussion session:
- Data collection and integration
- Developing a data strategy
- Data Governance
- IoT and Sensors
- IT/OT Convergence
- AI and Machine Learning
- Data Collaboration
- Monetising your data
- Predictive & Advanced Analytics
- Digital Twins
- Data Cyber Security
- Leadership Skills
A deep dive into the value of data and the importance of it in an organisation.
- Bringing transparency to business data through data quality measurement and analytics enables an organisation to see the impact of poor data on the business result
- A single source of truth provides credible, holistic data insights and removes barriers caused by complex systems landscapes
- Integrating data with collaboration partners can build trust and strengthen relationships through the delivery of a common goal
- How to improve data transparency and organisation?
- What is best practice for standardising processes?
- How to Incentivise data-driven practices?
Delegates choose from the same 12 topics for their third and final discussion session:
- Data collection and integration
- Developing a data strategy
- Data Governance
- IoT and Sensors
- IT/OT Convergence
- AI and Machine Learning
- Data Collaboration
- Monetising your data
- Predictive & Advanced Analytics
- Digital Twins
- Data Cyber Security
- Leadership Skills