To effectively leverage data as a strategic asset, CDOs must ensure that the C-Suite has a deep understanding of the data and how it can inform business decisions. In this session, we will explore the strategies that data leaders must take to engage the C-Suite and improve decision-making through increased data understanding and accessibility, including:

• Managing C-Suite expectations through effective education and addressing concerns about data quality and accuracy
• Building strong relationships with C-Suite stakeholders by communicating the value of data in business terms
• Developing user-friendly data tools and dashboards to increase data visibility and accessibility
• Funnelling intelligence through the business to communicate effectively with the C-Suite

Sanjeevan Bala, Group Chief Data & AI Officer, ITV
Steve Janoo, Chief Data Analytics & Digital Technology Strategy Officer, Diageo
Martin French, Chief Data Officer, Apex Group

This session will explore key strategies that Chief Data Officers (CDOs) 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.

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

Chief Data Officers 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

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

With the ever-increasing amount of data being generated and collected, ensuring data quality, security, and compliance has become more challenging than ever before. That's where data governance plays a critical role in optimising data-driven decisions.

This boardroom will examine how embracing a single context of data is crucial in setting the groundwork for innovation. Providing everyone access to the same data, understanding its context to better collaborate, share insights, and drive innovation.

• Examining strategies for effective data governance, including data quality, security, compliance, and privacy
• Defining data policies, assigning ownership and responsibility, and establishing processes for monitoring and reporting
• Mapping a journey to a "single context of data" to make data accessible for the whole enterprise
• Optimising data-driven decisions and supporting business goals through effective governance
• Engaging all stakeholders in your data governance strategy to effectively mitigate compliance challenges

Muhammad Saleem, Head of Data Architecture, BAE Systems Digital Intelligence

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

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 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
• 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.

As AI becomes more prevalent in business operations, it is essential for us to address the ethical implications of these technologies. Ensuring that AI systems are free from bias and are designed to operate within ethical guidelines is crucial for building trust with customers, employees, and stakeholders. Key Strategies:

• Defining Ethical Guidelines for AI systems that align with the organization's values and priorities
• Ethically Aligned Design to guide ethical decision-making.
• Identify potential biases in AI systems and take steps to mitigate them
• Ensuring transparency in AI systems, allowing stakeholders to understand how decisions are made and providing explanations for decisions where necessary
• Monitor and evaluate AI systems on an ongoing basis to ensure they are operating within ethical guidelines and are free from bias
• Establish governance structures for AI systems, including policies, procedures, and oversight mechanisms.

Detlef Nauck, Head of AI & Data Science Research, BT

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 e 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.

Richard Davis, Chief Data Officer, Ofcom

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

Chief Data Officers must leverage the right tools to quickly connect disparate structured and unstructured sources, building data models that suit the needs of the consumer, across multiple sources. In this session, we will explore how data virtualization could hold the key to supporting your organisational digital objectives, including:

• Cataloguing your entire data ecosystem to understand the sources and the relationships between them
• Providing a single view of the data by connecting disparate data sources
• Building data models that suit the needs of the consumer, ensuring data consistency and quality
• Providing real-time access to data, enabling agile decision-making and faster response times
• Ensuring data governance, data security, and data privacy are upheld throughout the virtualization process

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

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

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

Detlef Nauck, Head of AI & Data Science Research, BT

Join us for this exclusive fireside chat with Richard Davis, Chief Data Officer at Ofcom, as he shares exclusive insights into their journey to transform the culture across the regulating body. With so much data being regularly ingested, how can Richard and his team ensure they are aggregating the data effectively, and reporting it back through the business in a way that adds demonstrable value. Taking Ofcom on a journey to further upskill it's talent to increase their understanding of data and to move towards a self-service approach that champions innovation and augments decision-making. Richard will share how Ofcom is embracing emerging technologies such as NLP, Predictive Analytics and Machine Learning to continually provide a better service to all stakeholders, both internally and externally, in a rapidly shifting regulatory environment.

• Promoting Data Literacy to give employees the necessary skills to interpret data and make informed decisions at all levels of the organization
• Providing managers with the tools to upskill their talent and identify data challenges internally
• Building a training program for employees to move your workforce towards a self-service data platform
• How can you ensure leadership buy-in to your cultural transformation and realistically set expectations to manage and overcome resistance to change
• Ensuring data is aggregated accurately, and is 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

Richard Davis, Chief Data Officer, Ofcom