Explore a transformative shift in healthcare with Ranjit Gill, CIO of the AAH (Hallo Healthcare Group) and Pete Lydon, Director Sales Engineering at Actian. This session highlights Hallo's adoption of a cloud-first strategy, effectively managing over 21 million billing entries and thousands of daily orders. Learn how cloud analytics has not only streamlined massive data flows but also significantly enhanced patient service delivery, establishing new benchmarks in healthcare efficiency and responsiveness.

See how AAH's cloud strategy optimizes data handling and patient care. Join us to discover the future of healthcare efficiency!

Telenet, an affiliate of Liberty Global, is a market leading telecom known for its continuous customer-centric innovation using AI and data analytics. As an early adopter of Snowflake, they use data to drive cutting edge innovation such as hyper personalized customer services and privacy compliant data sharing with networking and broadcast partners. To further spur innovation, Telenet wants to make it easier for analysts and AI engineers to find and access data. In this session you will learn how Telenet is using Snowflake, AWS and Raito to give data analysts and AI engineers access to data in a fast and secure way.

For over a decade organisations have been managing their most valuable data assets with Cloudera. That means that the most valuable data under management has never been accessible to the latest wave of AI. Now is the time to unlock the potential of Enterprise AI. Let's make data more accessible than ever before, let's lower the bar to access and bring data, analytics and augmented business intelligence to the whole Enterprise.

Adam will share real-world stories of how organisations like Salesforce have combined analytics data and storytelling to influence change.

While digital transformation has made data essential for growing and improving your business, influencing change still means winning your coworkers' and executives' hearts and minds. This requires more than dashboards and spreadsheets. In this session, Adam Greco, an analytics industry veteran, will share real-world stories of how organisations like Salesforce and others have combined analytics data and storytelling to influence change.

Travel Management Companies (TMCs) are specialist travel providers that manage the business travel requirements of corporations of all sizes. They book and manage air travel, hotel stays, car hire, rail and other trip components for companies with varying budgets, traveller populations, policy requirements and service expectations, and deliver value in being able to control travel spend through policy management (e.g. class of travel), profile management (e.g. individual preferences), traveller tracking and delivering centralised booking and invoicing solutions.  

A standard, linear model of data provision exists ubiquitously in the corporate travel industry whereby TMCs provide reporting to analyse and consolidate spend and adjust policy. Data is provided in standard formats, with little focus on specific customer questions and travel policy management is retrospective and antiquated. 

In this presentation, delegates will see how Take2Eton is re-engineering our data landscape. From what started as project to improve our reporting and analytics platform by centralising data using a low code, highly governed, adaptable platform, we have now built a booking app, policy engine, data management app and data consolidation tool from ground up, improving customer interaction with our data at all stages of the lifecycle.

With AI tools constantly evolving, the potential for innovation seems limitless. But with great potential comes significant costs, and the question of efficiency and scalability becomes crucial. How can you ensure that your AI models are not only pushing boundaries but also delivering results in a cost-effective way? What strategies can help reduce the financial burden of training and deploying models, while still driving meaningful business outcomes?  Natalia Vassilieva is the VP & Field CTO of ML at Cerebras Systems. Natalia has a wealth of experience in research and development in natural language processing, computer vision, machine learning, and information retrieval. As Field CTO, she helps drive product adoption and customer engagement for Cerebras Systems' wafer-scale AI chips. Previously, Natalia was a Senior Research Manager at Hewlett Packard Labs, leading the Software and AI group. She also served as the head of HP Labs Russia leading research teams focused on developing algorithms and applications for text, image, and time-series analysis and modeling. Natalia has an academic background, having been a part-time Associate Professor at St. Petersburg State University and a lecturer at the Computer Science Center in St. Petersburg, Russia. She holds a PhD in Computer Science from St. Petersburg State University. Andy Hock is the Senior VP, Product & Strategy at Cerebras Systems. Andy runs the product strategy and roadmap for Cerebras Systems, focusing on integrating AI research, hardware, and software to accelerate the development and deployment of AI models. He has 15 years of experience in product management, technical program management, and enterprise business development; over 20 years of experience in research, algorithm development, and data analysis for image processing; and  9 years of experience in applied machine learning and AI. Previously he was Product Management lead for Data and Analytics for Terra Bella at Google, where he led the development of machine learning-powered data products from satellite imagery. Earlier, he was Senior Director for Advanced Technology Programs at Skybox Imaging (which became Terra Bella following its acquisition by Google in 2014), and before that was a Senior Program Manager and Senior Scientist at Arete Associates. He has a Ph.D. in Geophysics and Space Physics from the University of California, Los Angeles. In the episode, Richie, Natalia and Andy explore the dramatic recent progress in generative AI, cost and infrastructure challenges in AI, Cerebras’ custom AI chips and other hardware innovations, quantization in AI models, mixture of experts, RLHF, relevant AI use-cases, centralized vs decentralized AI compute, the future of AI and much more.  Links Mentioned in the Show: CerebrasCerebras Launches the World’s Fastest AI InferenceConnect with Natalia and AndyCourse: Implementing AI Solutions in BusinessRewatch sessions from RADAR: AI Edition New to DataCamp? Learn on the go using the DataCamp mobile appEmpower your business with world-class data and AI skills witha...

This past year was one of technology’s most exciting with the emergence of generative AI, as leaders everywhere considered the possibilities it represented for their organisations.

While many have already recognised its value and are eager to continue innovating, others are inspired by its potential and are seeking ways to adopt it

To implement a successful AI analytics strategy, three key ingredients are essential: powerful AI models, clean data, and a data culture ready to leverage these solutions.

Join us as we examine the challenges and opportunities data leaders face in preparing their organisations for the AI era.

In this episode, host Jason Foster sits down with Steven Pimblett, CDO at Rightmove, to discuss how data and AI can be leveraged as an asset to create value in a company. They explore the different approaches that CDOs take in implementing new data practices into an organisation, as well as the process of creating and demonstrating data value.  Additionally, they examine the shifts in marketing efficiency and data monetisation that have resulted from increased digitisation.

Cynozure is a leading data, analytics and AI company that helps organisations to reach their data potential. It works with clients on data and AI strategy, data management, data architecture and engineering, analytics and AI, data culture and literacy, and data leadership. The company was named one of The Sunday Times' fastest-growing private companies in both 2022 and 2023, and recognised as The Best Place to Work in Data by DataIQ in 2023.

In this flagship Big Data LDN keynote debate, conference chair and leading industry analyst Mike Ferguson welcomes executives from leading software vendors to discuss key topics in data management and analytics. Panellists will debate the impact of Generative AI, the implications of key industry trends, how best to deal with real-world customer challenges, how to build a modern data and analytics (D&A) architecture, how to manage, produce, share and govern data and AI, and issues on-the-horizon that companies should be planning for today.

Attendees will learn best practices for data and analytics implementation in a modern data-driven enterprise from seasoned executives and an experienced industry analyst in a packed, unscripted, candid discussion.

Data is transforming the world of work and creating new opportunities for individuals and organisations. However, to harness the power of data, one needs to develop the right skills and mindset. In this panel discussion, four experts from different sectors and backgrounds will share their insights and experiences on how to foster a culture of data-driven decision making and empower employees to use data effectively; how to identify and develop the technical, analytical, and soft skills that are essential for data professionals; how to address the talent gap and build a future-ready workforce that can leverage advanced analytics tools and techniques and how to leverage data skills to advance your career goals and create value for your organisation.

Join us as we unlock the secrets of data-driven strategies that drive profit, loyalty, and hyper-personalised experiences, with Capgemini and a Women in Data leadership panel.

At this year’s Big Data London, Women in Data & Capgemini are back with another must-see panel, featuring a diverse and engaging group of female data leaders and their allies from across the Retail & CPG worlds. Last year’s session was one of the most oversubscribed events of the day, with standing room only, thanks to its thought-provoking and honest discussions. This year’s panel promises the same dynamic as they tackle the conundrum of balancing margin focus with rewarding customer loyalty and how data plays a key role. 

The panellists, as well as sharing their own career journeys and experience, will explore how they’ve approached bold strategies that move beyond immediate profits to emphasise the long-term value of customer data and loyalty. They’ll explore how data, analytics & ai can uncover deep insights into customer behaviours and preferences, enabling brands to create personalised experiences and loyalty programs that boost engagement and build lasting trust. 

The discussion will highlight the importance of seeing customer data as a strategic asset. By investing in data collection and analysis, companies can identify trends, predict future behaviours, and tailor their offerings to meet evolving customer needs. This approach can drive repeat business and increase customer lifetime value, ultimately leading to higher margins over time. 

This year’s panel will explore the how data and boldness are key for a balanced strategy that blends margin management with a robust focus on customer loyalty. Using data smartly is key to achieving sustainable profit growth and strengthening brand loyalty. Don’t miss out on what promises to be an inspiring and insightful discussion! 

Join us to explore why Analytics as Code is the future of BI & learn how to make it a core component of your analytics engineering strategy.

Building visualizations in a BI tool is just the beginning. To create truly innovative data products, we must blend BI and data pipelines into a reactive, composable end-to-end system. Such a system adapts to changing business conditions, evolving technologies, and increased scale to meet customer needs. Join us to explore why “Analytics as Code” is the future of BI and learn how to make it a core component of your analytics engineering strategy.

Across multiple industries, time and again Data and Analytics teams find it difficult to setup and execute experimentation programs at scale in order to drive sustainable, data-driven growth. A significant challenge we have identified is the limited time teams have to focus on new ideas, challenges and R&D, with BAU responsibilities often taking priority. In this panel, we will explore ways that both Twenty First Group and Motorway have tried to address this issue by giving their Data and Analytics teams protected time, spaces and roles to enable these longer term development goals. In partnership with Women in Data we will explore how to best identify that critical (female) talent that can help facilitate these kinds of initiatives and how we can continue to empower our teams to succeed in an ever-changing industry.

We’ve never had more data, and we’ve never had more immediate access to data thanks to the success of the Kafka protocol. But what use is data if you can’t process it quickly enough to make a difference? Or can’t handle the scale with which it’s being generated? Or can’t make robust ACID-grade decisions if the situation requires it? 

Volt Active Data is a real time decisioning platform that’s been around for a decade now, and plays a silent role in the lives of over a billion people every day. It’s used to run the prepaid mobile phone system for over 700 million end users, control millions of energy meters in Europe, and provide real time user analytics for over 500 million video game users worldwide. 

In this session we’ll show how Volt’s new Stream Processing component allows you to connect the most powerful information pipeline (Kafka) to the most powerful real time decision engine (Volt).

Why does this lead to value? The Kafka-verse is very good at telling us about disjoint events in the recent past, but is short of tools to turn all that raw data into a clear understanding of what’s happening right now. Volt is excellent at the kind of tasks you need to solve if you want to get to ‘right now’. Complex aggregations, joining streams of imperfectly related data, enrichment, filtering, routing and other aspects of ‘Data Plumbing’ are easy with Volt. Once you have a clear and robust view of ‘right now’ you can get Volt to make real time decisions, at scale and with 100% ACID consistency that allow you to make the most of your newfound understanding.

Volt is more than just a stream processing platform. It started out as a performant, scalable and 100% ACID in memory database before evolving into a real time decision engine. Now, thanks to our new Stream Processing module you can get Volt to operate at the scale of your business, with the response times needed for success and the reliability your customers and stockholders expect.

Everything has changed in the last year with Generative AI entering onto the scene. This means a re-shuffling of priorities and budgets, putting AI-enabled Data & Analytics right back at the top of the agenda. In this session we will discuss: 

• That there is no Generative AI without data – but it has to be the right data 

• The importance of being able to bring together organised and trusted data 

• Why your data integration strategy is the foundation to successfully using AI

Gen AI entering the scene means a re-shuffling of priorities & budgets, putting AI-enabled Data & Analytics right back at the top of agenda.

Discover how D&G's diverse leadership has unified our data team by leveraging advanced tools and AI technologies. Learn how we foster a collaborative culture that drives innovation and impactful outcomes through state-of-the-art strategic analytics and AI-driven insights. Join us to explore strategies for integrating cutting-edge tech with diverse perspectives to enhance team performance and achieve impactful business and customer outcomes.