Programme @ Enterprise AI & Big Data

Invite to be extended to Vincent Camrose, Minister for AI and Intellectual Property, Department for Science, Innovation and Technology, UK Government

• How to enable Gen AI to reshape the Enterprise
• How can you harness the power of generative AI without risking your data, processes, governance and culture?
• Leveraging AI as a path to Enterprise re-invention
• Unpacking the accessibility of tools and platforms like ChatGPT: Is the price of Generative AI worth the payoff

• Debunking the Myths between AI and Machine Learning and exploring the differences between both
• Achieving Scalability in ML/AI adoption by deploying a comprehensive Data strategy

• Exploring the synergistic relationship between AI and Big Data
• AI in the Enterprise- Unleashing opportunity through data
• Creating a holistic strategy that includes AI, BI, ML and other disruptive technology processes and capabilities.

• Strategies for striking a balance between leveraging third-party capabilities and developing in-house models
• How to choose between open source and proprietary technologies
• Techniques for identifying suitable use cases, delivering tangible business value, and fostering trust in AI-driven solutions

• How to build AI systems collaboratively.
• Building Trust Through Explainability for AI and Digital Transformation
• Overcoming hesitation to deploy AI-powered solutions.
• Developing an Effective AI Governance Structure

View Seminar Sessions

• How is AI used in cyber security and what are the key applications for AI in Cybersecurity
• Harnessing machine learning and deep learning techniques to analyse network behaviour and identify deviations or security incidents from the norm thus allowing for immediate response and enhancing future security measures by blocking potential threats with similar traits
• Navigating the complexities of AI Security Testing
• Cybersecurity considerations for AI

• Customer data strategies in the era of ‘Digital First’
• How to monetise your Big Data strategy leveraging AI on your customer journey
• Building your Big Data Platform and plugging into your AI strategy with the customer in mind

Data storytelling, as an approach, is becoming more attractive as a way to make entire organisations data-driven.

Turning data into information and providing insights to everyone underpins analytic strategies everywhere.

Often the reality is falling some way short of aspirations.

How do we transform data into stories that everyone understands and has confidence in?

At the same time, how can we use technology to support the cultural shift where data-driven decisions are part of everyone’s day-to-day roles?

In this session, we’ll look at what BI functions you should look for to create information and trust.

How do we lower the barriers between data and information consumers?

And ultimately how do we build confidence with everybody in our organisation which will help them to see the value in basing their actions on data-driven insights?

So, you have a lot of data about consumer behaviour on your tech platform. How do you go from that raw data to getting value? That’s what this talk is about.

Vidhya will share the approach YouView has taken and bring this to life with project examples.

• Mastering your approach to data exploitation
• Making use of data insights use cases
• Key considerations for an insight strategy that delivers value

Service assurance and providing a stellar customer experience are some of the key challenges facing the enterprise today.

As customers are highly dependent on being provided with a dynamic and reliable online experience- a trend accelerated by the Covid-19 pandemic- the availability and quality of these services is important to them.

AI can breathe new life into the industry and how they run their quality assurance.

In this presentation, we will discuss:

• How can AI help improve operational stability?
• How can AI drive value?
• What does the deployment and launch of new converged products look like in the age of AI?

Because of the cost-saving benefits, competitive advantages, and new market opportunities, many data leaders feel the pressure to accelerate cloud adoption.

However, implementing hybrid and multi-cloud strategies is daunting—incompatibility between diverse systems introduces too much complexity, and traditional ETL tools are slow and resource-intensive.

While you gradually adopt the cloud, you can still deliver immense business value and actionable insights without impacting existing on-premises SAP ERP, CRM, HCM, SCM, and other enterprise applications.

By building real-time data pipelines, you can meet current demands while setting the foundation for the future.

During this session, you will learn:

• How to implement a continuous data streaming method that securely and efficiently leverages data residing in SAP and other on-premises enterprise applications without impacting them
• How advanced log-based CDC technology securely accelerates high-volume data delivery in complex environments so it’s available in real-time for immediate decision making, advanced analytics, and ML/AI
• Real-world examples of how hundreds of organizations leverage analytics to extract value from legacy systems to achieve a more dynamic and agile business

How to augment intelligence with a different approach to machine learning

For many, machine learning and AI remain an arid frontier, particularly in respect of attempts to model expert human judgement.

In organisations where data is unstructured, and poorly managed and outcomes always variable, big data statistical machine learning approaches have found the terrain difficult to navigate and thrive in.

Where big data is believed to be fundamental to developing AI we will look at:

• What small datasets and human expertise can combine effectively
• an area of machine learning development that does not exclude human expertise; and
• the business benefits of taking on AI projects