- The strategies that forward-thinking technology leaders employ to guide their organisations through complex landscape of digital transformation
- Explore the visionary approaches that are shaping the future of enterprise technology
- How we are harnessing the power of emerging technologies such as AI
- Fostering a culture of innovation while ensuring data security, scalability and sustainable growth

- Explore the intricacies of migrating and managing data in the cloud while prioritising security

- Look at proven strategies and best practices for a seamless and secure data transition, covering areas such as encryption, access controls and compliance

Data leaders must leverage the right data management strategies and technologies to create efficiencies, reduce costs, and enable AI adoption across multi-cloud and hybrid environments. In this session, we will explore the strategies and technology that data leaders must take to achieve effective data management, including:

• Building a comprehensive data management strategy that includes data governance, metadata management, and data lineage
• Leveraging AI and machine learning to automate and streamline data management processes
• Creating a data platform that supports multi-cloud and hybrid environments
  Implementing cost-effective storage solutions that balance performance and cost

Connecting data sources seamlessly is essential for enterprises seeking to accelerate their time to insight, protect customer data, and deliver effective data governance. CDOs must leverage the right strategies and technologies to seamlessly move and integrate data into a centralised architecture. In this session, we will explore the steps data leaders must take to achieve seamless integration, including:

• Using automated, reliable, and scalable data movement platforms to accelerate your insights
• Integrating data into a cloud-based architecture like a data lake or data warehouse
• Ensuring data quality and consistency through governance processes
• Aligning data integration with business objectives and KPIs

This session will explore key strategies that Data leaders can use to deliver accessible insights at scale to their organization, allowing them to make faster and more informed decisions.

• Educating stakeholders about the value of data and providing access to data-driven insights to empower employees to make data-driven decisions.
• Leveraging Advanced Analytics and developing machine learning models to identify patterns and trends in data, as well as predictive analytics to forecast future trends.
• Democratizing access to data for all stakeholders across the organization
• Developing self-service analytics platforms for stakeholders to access data-driven insights.

Enterprises across all industries are seeking ways to improve their operations, increase efficiency, and deliver better customer experiences. One of the most promising technologies for achieving these goals is Generative Artificial Intelligence (AI). In this keynote, we will explore the new age of digitalization and the role of Generative AI in driving enterprise innovation.

- The basics of Generative AI and its potential for enterprise transformation

- Real-world examples of how enterprises are using Generative AI to innovate and drive growth

- How to assess your enterprise's readiness for Generative AI adoption

- Key considerations for implementing Generative AI solutions in your enterprise

- Best practices for managing the human-machine interface in Generative AI applications

As more data is collected, processed, and shared, CDOs must navigate a complex landscape of fresh risks and challenges to ensure that their enterprises are protected from security threats, cyber attacks and data breaches. In this session, we will explore the strategies that data leaders must take to secure their enterprises in the data-driven age, including:

• Developing a comprehensive data security and privacy strategy fit for a multi-cloud and hybrid environments
• Establishing policies and procedures for data access and use
• Educating employees on data security best practices & ensuring compliance
• Partnering with cybersecurity experts to stay ahead of evolving threats

In this session, we will explore the art of communicating the value of AI and data analytics projects to leadership particularly when it comes to demonstrating return on investment and quantifying the benefits to the organization. Examining the key elements of a successful communication strategy, understanding your audience, framing your message, and using data to support your claims.

- Developing a clear business case using data-driven metrics to measure success, and leveraging effective storytelling technique

- Identifying easy wins from your use cases to demonstrate a quick ROI

- Linking the value of your projects to drive strategic business outcomes to achieve buy-in

- Exploring the latest trends and technologies in AI and data analytics, and how to stay ahead of the curve

Explore the critical role of platform and architecture in harnessing the power of these technologies to unlock data-driven insights, drive innovation, and shape the future of your organisation.

• Understand the significance of a robust platform and architecture for advanced analytics, AI, and LLM implementation
• Explore key considerations for building an effective platform that supports scalability, flexibility, and agility
• Learn about the architectural components necessary to maximize the potential of new technology
• Discuss real-world use cases, success stories, and lessons learned from organizations at the forefront of these technologies
• Identify challenges and potential solutions for implementing and managing advanced analytics, AI, and LLM platforms

- Gain a comprehensive understanding of modern BI strategies that can assist in driving growth and innovation within your organisation

- Explore how to leverage Business Intelligence tools, data virtualization and predictive analytics to uncover actionable insights, enhance operational efficiency and gain the competitive edge

- Learn how to foster a data-centric culture through the latest trends, challenges and opportunities in BI

Explore the key challenges data leaders face when building a data-driven culture across their enterprise, and discover best practice for overcoming their obstacles to embed a data-centric operating model and mindset.

• Promoting Data Literacy to give employees the necessary skills to interpret data and make informed decisions at all levels of the organization
• Leadership buy-in and effective communication to manage and overcome resistance to change
• Breaking down data silos to establish a single source of truth for data
• Ensuring data is accurate, complete and up-to-data to deliver consistent data quality to deliver reliable insights
• Building trust in data with established data governance processes and procedures

- As organisations increasingly look to AI to improve business processes efficiency and productivity, we must ensure that AI is used responsibly. What is considered to be an ethical approach to AI?

- Discuss the principles to be evaluated by your organisation to ensure the use and development of AI remains ethical

- Explore the challenges of ethical governance when dealing with data and machine-driven services

Increasingly senior executives are pushing new machine learning initiatives to drive business value, leaving Chief Data Officers responsible for finding new ways to accelerate its adoption across the entire lifecycle, from data preparation to model deployment. This session will explore key strategies that CDOs must take to build a framework that enables them to develop, test, and deploy machine learning models at scale.

- Preparing and cleaning data using data cleaning and transformation tools to pre-process raw data

- Creating a structured data pipeline that can handle large volumes of data.

- Develop and test machine learning models, focusing on accuracy, performance, and scalability

- Deploying and scaling machine learning models effectively, using containerization and orchestration technologies

- Implementing a Continuous Integration and Deployment (CI/CD) pipeline for machine learning models, allowing for automated testing, deployment, and monitoring

- Considering ethical considerations including bias, fairness, and transparency to ensure that models are ethical and unbiased.

One of the biggest challenges that CDOs face is ensuring consistent data quality and availability across the enterprise. Data must be accurate, complete, and available when needed, at all levels of the enterprise. This session will explore how CDOs can establish a strong data quality framework to maximise the value of their analytics and insights.

- Defining data governance and quality standards, data ownership, and data stewardship responsibilities, including policies and procedures for data management, data security, and compliance

- Implementing data quality controls that monitor the accuracy, completeness, and consistency of data and conducting regular data audits.

- Integrating data across the enterprise, so that it is easily accessible across different departments and applications

- Creating transparency of the enterprise data estate including the data flows in a centralised data catalogue

- Leveraging data analytics to identify patterns, trends, and insights that can inform business decisions and using data visualization tools to present data in a meaningful way.

- Providing training on data management best practices, implementing self-service analytics tools, and ensuring that data access controls are in place.

- Delve into the transformative capabilities of generative AI and how Data leaders can leverage these technologies to drive innovation within their organisation
- Explore how to harnes the power of generative AI and enhance data driven decision making and create valuable insights
- Drive strategic growth and gain insights into practical implementations, challenges and best practices

In today's complex regulatory environment, large UK enterprises must ensure compliance with a range of data protection regulations, including GDPR, CCPA, and HIPAA. Appointing a Data Protection Officer (DPO) is a necessary requirement for enterprises to navigate these regulations and protect their customers' sensitive data. However, finding qualified DPOs and ensuring compliance with multiple regulations can be a significant challenge. In this session, we will explore the strategies that data leaders must take to manage continuous compliance and reduce risk, including:

• The role of a DPO in ensuring compliance with GDPR, CCPA, HIPAA, and other data protection regulations
• The challenges of appointing a qualified DPO and building an effective compliance program
• The benefits of outsourcing the role of DPO to a third-party service provider, including access to qualified experts, cost savings, and reduced risk
• The importance of building a strong culture of data protection and privacy within the enterprise Best practices for managing compliance across multiple regulations and jurisdictions

- How AI driven insights and strategies are revolutionising industries and empowering decision making
- Explore the potential of AI to enhance productivity, optimise operations and create new opportunities
- Addressing ethical considerations and challenges that come with this transformative technology