Name: What Is To Be Done When Absolutely Everything Can Be Faked?
Start: 2019-07-04T09:30:00Z
End: 2019-07-04T09:30:17.000Z
Location: BrightTALK
Rating: 4

Dataiku is the Universal AI Platform, uniting the technology, teams, and operations needed for companies to build intelligence into their daily operations, from modern analytics to generative AI. Together, they design, develop and deploy new AI capabilities, at all scales and in all industries. Organizations that use Dataiku enable their people to be extraordinary, creating the AI that will power their company into the future. 

More than 700 companies worldwide use Dataiku, driving diverse use cases from predictive maintenance and supply chain optimization, to quality control in precision engineering, to marketing optimization, generative AI customer proof, and everything in between.

Operationalize Agentic AI Without Compromising Control

Leading financial institutions are moving beyond disconnected tools to deploy scalable, governed AI agents that deliver real business value. Make sure you are one of them!

From risk scoring to personalized offers, Dataiku and Snowflake help organizations build agentic workflows that prove that it's possible to innovate fast without sacrificing oversight, See how it's done and discover real-life examples in this joint guide.

Financial Services AI Agents: The Dataiku + Snowflake Approach

GenAI is transforming financial services, but only when guided by the right guardrails. Join Dataiku and Celestial Systems to learn how leading financial institutions are safely and efficiently modernizing operations with GenAI, driving real-world impact through use cases like summarization, report generation, and customer service automation. 

Designed for financial services leaders tasked with balancing innovation and compliance, this webinar will show how to adopt GenAI rapidly while staying fully aligned with enterprise controls, risk frameworks, and regulatory standards.

What You'll Learn

•How platforms like Dataiku enable governed AI
•How Celestial helps financial institutions build a GenAI roadmap that works
•Real-world use cases in finance

Powered by:

Dataiku: The Universal AI Platform™ Unlock the creation of analytics, models, & agents that people trust, with the control you need to scale.

Celestial: Celestial is your strategic partner for building and scaling AI, combining deep technical expertise with a sharp focus on delivering measurable business impact across the enterprise.

The GenAI Advantage: Smarter, Safer Modernization in Financial Services

Financial institutions are moving from AI exploration to tangible business impact. In this live session, experts from Celestial Systems, Dataiku, and Digital^Shift will share real-world examples of how leading banks, credit unions, and insurers are using AI to enhance customer experience, streamline lending, and strengthen risk management.
You’ll learn how to:

•Build an AI strategy with proven use cases reshaping banking, insurance, and wealth management.

•Streamline loan origination and credit processes using AI for measurable business outcomes.

•Scale beyond proofs of concept with data readiness, governance, and modern infrastructure.

•See AI agents and automation in action driving efficiency across operations.

AI in Financial Services — From Vision to Value

See how leading enterprises are moving from Alteryx to Dataiku in a fraction of the time. Powered by v4c.ai, a trusted migration partner for global enterprises, the v4c Migration Accelerator enables up to 75% automation, ensuring faster, lower-risk transitions with minimal disruption. This webinar is tailored for executives driving cost reduction, operational agility, and data modernization at scale.

Leave Legacy Behind: Fast-Track Your Workflow Migration to Dataiku

Deploying GenAI and agents in financial services is challenging—balancing business needs, AI engineering, and compliance adds complexity.

Join Dataiku and NVIDIA experts for a lively discussion on how to seamlessly integrate GenAI and agents at scale across different compute environments and front-end applications. 

This session will feature a live demonstration of a money laundering detection use case, leveraging Dataiku’s LLM Mesh, accelerated by NVIDIA NIM and NeMo Microservices. Gain practical insights into balancing innovation and governance, and see how scalable GenAI solutions can transform compliance and risk management for financial services.

Key Takeaways:
•Live demo: Anti–money laundering detection using Dataiku’s LLM Mesh + NVIDIA NIM and NeMo Microservices
•Strategies to align business + engineering
•Tips to automate compliance workflows at scale

Dataiku & NVIDIA: Scaling AI Agents in Financial Services

This webinar explores how the strategic partnership of Dataiku, Snowflake, and Deloitte revolutionizes analytics stack modernization. Learn how Snowflake provides the unified data foundation, Dataiku enables advanced AI, GenAI, and intelligent agent development, and Deloitte offers expert strategy and implementation. Discover how this collaboration streamlines operations, enhances efficiency, and drives unprecedented business value from your data.

Modernize Your Analytics Stack With Dataiku, Snowflake, and Deloitte

The analytics landscape is evolving rapidly as organizations embrace modern, cloud-based tools to accelerate insights and innovation. Join our exclusive webinar to discover how Dataiku empowers teams to increase efficiency, unlock the potential of ML and GenAI, and maintain strong governance—all while attracting top talent. You’ll also see a live demo based on real-world examples of companies that have replaced legacy tools like SAS with Dataiku to drive smarter, faster analytics.

Future-Proof Your Analytics: Modernize With Dataiku

Shadow analytics is putting your enterprise data at risk. Without proper oversight, IT loses visibility and control over where and how data is being used across analytics workflows. Shadow analytics — when analytics happen outside IT governance — creates security gaps, compliance risks, and data silos, making it nearly impossible to enforce policies, protect data, and maintain enterprise-wide standards.

End Shadow Analytics and Regain Control Over Enterprise Data With Dataiku

Discover how AWS and Dataiku are enabling next-gen multimodal AI applications that combine text, image, audio, and video for smarter, more adaptive AI agents. This session will introduce Amazon Nova, a new family of foundation models in Amazon Bedrock, and explore its deep integration with features like RAG, fine-tuning, and agentic capabilities. Attendees will see how the Dataiku LLM Mesh connects seamlessly to Nova models for building enterprise-ready generative AI applications using entirely visual, code-free data flows.

Pioneering Next-gen Multimodal Agentic AI Applications with AWS and Dataiku

In this conversation, Florian Douetteau (Co-Founder & CEO of Dataiku) and Lynn Heidmann (VP Content & Product Marketing) unpack:

- Why designing an agent differs radically from one industry to another.
- How human-AI collaboration actually works in practice.
- Candid insights from common roadblocks moving from testing to production.

Whether you're just exploring the concept of AI agents or navigating the road to deployment, this video brings you the insights you need to move forward, faster.

Enterprise AI Agents in March 2025: Let's Debunk the Hype

In this hands-on webinar, discover how AI agents allow us to rethink data interactions. Experience how Dataiku allows you to build business-purpose AI agents that transform complex data into intuitive, conversational experiences and full automation while ensuring reliability and security.

Building an AI Agent in Dataiku

In this webinar, we'll walk you through a live demo showcasing how an AI agent can use tools like dataset lookup, web search, and email notifications to take action and deliver results — fast. Whether you're looking to automate tasks, streamline processes, or create custom solutions, this session is your ticket to mastering AI agent workflows in Dataiku.

Inside the AI Agent Toolbox

AI agents promise automation and efficiency, but how can enterprises utilise them while maintaining control? This session explores the evolving role of agents, their distinction from GenAI, and the key enablers businesses must set in place to maximise the generated value.

AI Agents - Making Them Work in an Enterprise Environment

2025 marks a pivotal year for generative AI, transitioning from revolution to reckoning, with trends like AI agents, ROI challenges, and governance shaping its future. This webinar explores these dynamics with industry data and real-world examples, equipping attendees to avoid the "commodity trap" and lead in the age of agentic AI with innovative, ROI-driven applications.

5 GenAI Trends That Will Shape 2025

Join us for an exclusive webinar designed for data professionals considering migrating from SAS to Dataiku powered by the Corios Analytics Modernization Platform (AMP). In this session, we will explore the key benefits and best practices of making the switch, ensuring a smooth transition while maximizing your analytics capabilities.

Bridging the Gap: SAS to Dataiku Migration with Corios

With 90% of senior AI leaders investing in Generative AI (GenAI), this technology is now a cornerstone of modern business strategy. An annual survey from Dataiku and Databricks builds on last year's insights and reveals how organizations are evolving their GenAI usage. From shifting budget priorities to tracking ROI and discovering new use cases, the report provides a comprehensive view of the rapidly changing GenAI landscape.

AI by the Numbers: Cracking the GenAI Code for Business Growth With Dataiku and  Databricks

In an era where Generative AI is revolutionizing industries, the life sciences sector stands to benefit immensely from AI-powered solutions. This webinar, jointly presented by AWS and Dataiku, delves into building AI-driven chatbots in the life sciences domain.
Participants will gain insights into the latest advancements in the Generative AI space, underpinned by robust AI and machine learning frameworks. Experts from AWS and Dataiku will demonstrate how these intelligent chatbots can streamline research, enhance patient engagement, and improve operational efficiencies within life sciences organizations.

This webinar is designed for data scientists, AI enthusiasts, and professionals in the life sciences sector seeking to harness the power of AI to drive innovation and operational excellence. Join us to explore how AI-powered chatbots can reshape the future of life sciences.

Building AI-Powered Chatbots for Life Sciences Applications

Join us for an exclusive webinar where we reveal an exciting new chapter in our journey with our partner community, a pure-play strategic services partner, v4c.ai 

About the Webinar:
Hear how v4c.ai emerges as the next generation of a Dataiku boutique services partner
Learn how v4c.ai brings unique industry expertise to drive business value to Dataiku customers
Learn more about the Dataiku migration tool 
Dive into the stories of success with current v4c.ai customers in the era of GenAI and how Dataiku has impacted their businesses

See Why Dataiku Is a 2024 Gartner Magic Quadrant Leader.

Next Generation AI: How v4c.ai and Dataiku are teaming up to deliver solutions for today and tomorrow

AI technologists must consider the ethical implications of what we’re building. Kurt Muehmel explores AI within a broader discussion of the ethics of technology, arguing that inclusivity and collaboration is a necessary answer.

Toward Ethical AI: Inclusivity as a Messy, Difficult, but Promising Answer

The use of AI in industry and society is growing, and so are the concerns about its impact. The Information Commissioner’s Office (ICO) is responsible for protecting individual’s data protection rights, and has been at the forefront of tackling complex privacy challenges with significant societal implications, including the Facebook/Cambridge Analytica investigation for example. 

The ICO has made AI a priority for the organisation and, with the new powers given to us through the GDPR, we are developing an enhanced supervisory framework for assessing the risks and potential harms to peoples’ data protection rights that could occur when AI is used. The framework will cover many of the hot risk topics which are the focus of the EGG conference, including interpretability, bias, and fairness among others. 

This talk will inform the audience about the ICO’s work on AI, give an overview of our current thinking on some of the steps organisations can take to navigate AI’s data protection challenges, and encourage the audience to feed into the framework’s ongoing consultation.

GDPR and the ICO's Proposed AI Auditing Framework

There are plenty of studies that discuss the gender pay gap. But these studies can be frustrating because they don’t allow us to dig into the data to better understand how the gender pay gap trend manifests itself. This talk will explore the relevant datasets, let them speak, and help us understand better what we mean when we talk about the gender pay gap

Data Science Beyond Business: Navigating the Gender Pay Gap

After scanning more than fifteen million feet, two and a half million shoes from almost every brand and receiving more than two million of feedback points from consumers all over the world, SafeSize has managed to build a brilliant shoe discovery solution for omnichannel retail.

In this session, Antonis will share with the audience the key learnings and the main challenges that SafeSize faced the last decade while at the same time will explain how AI solutions could be implemented in the retail market today.

Building a Brilliant Shoe Discovery and Highlighting the AI in Retail

Future outlooks of financial KPIs are key to steer Mercedes-Benz business. In the past these outlooks where tediously collected and calculated with a lot of manual effort. Lately, such outlooks are often generated by Machine Learning based forecasts. After successfully working on more than 25 financial KPI forecasts, we packed all our knowledge into a software package. Using DataIku DSS we can put our package at the fingertips of our business users, enabling them to combine their business expertise with state-of-the-art Machine Learning.

Democratizing Automated Forecasting at Mercedes-Benz

In this talk, I will look at the contributions public service media organizations can play in the emerging understanding of the responsible and ethical practice of data science. We will look at some specific project examples: what works and where we can improve. 

Among them are automatic decision-making processes, as they need to come to Public Service Medias (PSM) because they represent some competitive advantage and competitive potential. But PSM are about making sure that people have a shared understanding of the world around them. How can you balance these two different expectations?

 By the end of the talk, the audience should have examples and principals they can apply in their own data science practice.

Ethics, Data Science, and Public Service Media

How are the privacy & ethical standards of Rabobank determined and protected and how can we effectively maintain our morals while at the same time we encourage a strong drive to optimize business opportunities and profitability?
 
In this session, we will look at a Privacy by Design canvas for Rabobank and look at examples for which it may not immediately be clear how to act. These examples include cases such as prediction of life-changing events (pregnancy, divorces, illness or worse), that motivated the enterprise discussion on Ethical AI.

Ethical Enterprise AI - A Guideline or Compass?

The Gaussian assumption in the Black-Scholes formula for option pricing has proven its limits. Today, Generative Adversarial Networks (GANs) are the new golden standard for simulation. It has worked wonders in image generation, but can it be applied to option pricing? Here is the story of how 2 data scientists (inc. a former trader) deployed a GAN for option pricing in real-time, in 10 days.

Generative Adversarial Networks for Finance

Making data science a success is really hard with up to 85% of projects and initiatives around big data and data science failing according to Gartner. The reasons are complex but often misunderstood. What is so different about data science that it needs new approaches?

A survey in 2016 concluded that 80% of data science is preparing and cleaning data (the infamous 80/20 rule). That survey of data scientists caught on and developed into the widely recognized problem statement for data science, because productionisation of models is the TOUGHEST problem in data science. This talk will introduce the unique data science requirements and why they are important for the long game and introduce the Rendezvous Architecture, a proven solution to integrate data science and enterprise requirements in a harmonious way at scale

How to Make A Success of Data Science: Rendezvous Architecture for Data Science

Working as a data scientist can be fun and exciting. You get hired and you have all these great ideas and projects that you would like to try out with all that big data lying around. A couple of weeks or even months later, things start to change. You start getting data engineering tasks, your projects and ideas get down-prioritized and you end up doing reporting and dashboards for executives. Does this sound familiar? If you are anything like Adrian, you might feel constrained by your environment; not to mention underused to your full potential.


In this session, Adrian will talk about his experiences and how a very old and unexpected book helped him understand the mechanisms that he can use to kill frustration, reduce stress and learn to give the maximum of his capabilities while adding value to the organization. He cannot promise you a "solution-fits-all" session, but what he DOES promise is an engaging, funny and honest session that will help you put things into perspective.

Leveraging the Law of Averages to Deal with Data Science Frustration

It is still early days for open source solutions for productionalising and deploying machine learning (ML) models, managing scalable data pipelines and data science experiments. Kubeflow is a collection of tools that are perfect for these use cases and is gaining popularity for a good reason. 

This talk describes a system built on top of Kubeflow which is generic enough to be used for managing ML pipelines of various shapes and sizes, yet flexible enough to allow entirely custom workflows. At its core, there is a set of conventions which determine where data is read from and written to, and expressing data preprocessing and models as a configuration of composable objects and functions. This approach makes it trivial to add new models, datasets, and training objectives to a production system, and enables training and deploying stacked models of arbitrary complexity.

Convenient and flexible ML pipelines with Kubeflow

The corporate smart-city rhetoric is about efficiency, predictability, and security. "You'll get to work on time, no queue when you go shopping, and you are safe because of CCTV cameras around you". All these things make a city acceptable, but they don't make a city great.

Goodcitylife.org is a global group of like-minded people who are passionate about building technologies whose focus is to give a good life to city dwellers; because the future of the city is, first and foremost, about people.

We go beyond the creation of a smart city by using digital data to measure intangible aspects of the urban space: the spirit of the city. We will show how this acquired knowledge can be leveraged to build new tools for both citizens and municipalities. Can we rethink existing mapping tools? Is it possible to capture smellscapes of entire cities and celebrate good odors? Can you measure a city's cultural capital?

We will see how a creative use of network-generated data can tackle hitherto unanswered research questions.

The Spirit of the City: Capturing Network-Generated Data for Better Cities

Synthetic data is becoming a prevalent technique to circumvent a major difficulty in organizations: how to manage and share good quality data without disclosing personal and sensitive information? 
Synthetic data solves this problem by generating fake data while preserving most of the statistical properties of the original data. In this session, we will introduce some metrics to quantify similarity, quality, and privacy.

Synthetic Data: How do We Manage Them?

Program in UK time:

15:50 - Organisation + Humans + Data - Building a highly effective people analytics team at Barclays
Jesús Rogel, Director of Data Science - Analytics and Insight, Barclays

16:10 - Mapping your organization’s enterprise AI maturity
Romain Fouache, COO, Dataiku

16:30 - Stakeholder Management: A Data Scientist's Perspective
Denis Fragkakis, Lead Data Scientist, IG

16:50 - Data Science: Fundamentals & Organisation - Afternoon Session
Peter Jackson, Director - Group Data Sciences, Legal and General

Livestream: EGG LDN 2019 - Advanced Analytics in the Field - PM Plenary Sessions

Program in UK time:

14:00 - Balancing AI and the Human Touch
Tim Hesse, Director of Data, carwow

14:20 - How to Build a Data Science Service Centre of Excellence
Nicholas Bignell, Director, UBS

14:40 - Cyber Risk Analytics: The Next Frontier
Paul Guthrie, Chief Technology and Product Officer, Envelop Risk

15:00  - Optimising smart cities with AI
Kim Nilsson, CEO, Pivigo

Livestream: EGG LDN 2019 - Data Science Fundamentals - PM Plenary Keynotes

Program in UK time:

11:15 - Data Science Pioneers: Conquering the Next Frontier
Kia Eisinga, Senior Data Scientist, TomTom
Shaun McGirr, Head of Data Science & Business Intelligence, Cox Automotive UK
Jan Teichmann, Senior Data Scientist, Zoopla
Luca Maria Aiello, Senior Research Scientist, Nokia Bell Labs

11:45 - The Growing Pains, Pitfalls & Future for a Data Science team in a Hyper-Growth company
Shaun Moate, Director of Applied Machine Learning, DAZN

12:05 - How Mercedes-Benz and Credit Suisse Super-Sized their Data Initiatives
Timo Gemmecker, Head of Business Analytics, Mercedes-Benz
Denis Avdonin, Director - Head of Analytics IT, Credit Suisse

Livestream: EGG LDN 2019 - Advanced Analytics in the Field - AM Plenary Sessions

Program in UK time:

09:00 - The Path to Enterprise AI
Jennifer Roubaud, VP NEME, Dataiku

09:10 - Algorithmic bias, privacy protection and EU non-discrimination law
Dr. Sandra Wachter, Senior Research Fellow in Data Ethics & AI, University of Oxford

09:30 - Enabling the data revolution     
Caroline Carruthers, Director, Carruthers and Jackson

09:50 - A Glance at ADA: Aviva’s Algorithmic Decision Agent
Damian Rumble, Senior Data Scientist, Aviva

10:10 -  Can We Make AI Likeable (at least enough to avoid the counter-revolution)?
Florian Douetteau, CEO, Dataiku

Livestream: EGG LDN 2019 - Data Science Fundamentals - AM Plenary Keynotes

EGG LDN 2019: The Human-Centered AI Conference

We like to believe it was once easy to distinguish authentic images from those doctored for a political purpose. We recall an age of so few news sources that none of them were fake. The rose-tinted glasses that enable our nostalgia to hide an important enduring lesson: the most important things you can learn about your data, you cannot learn from your data.

Thankfully, salvation is at hand if we only pay more attention to the second word in "data science". The scientific method is more than a technique for generating hypotheses to A/B test, it offers everything we need to use data responsibly, regardless of which algorithms are in fashion. In this talk, I share practical knowledge drawn from a background in social science, which can help any practitioner embed ethics in their daily work.

What Is To Be Done When Absolutely Everything Can Be Faked?

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What Is To Be Done When Absolutely Everything Can Be Faked?

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About this talk

Dataiku