Day 1 - 5 October 2022
10:00AM
(PDT)
Aneel Kumar
Senior Director, Product & Platform Engineering Services
Accenture

10:00AM - Day 2
View Applied Data & Analytics: Chairpersons Welcome
Chairpersons Welcome, AI, Data & Digital Strategies
Chairpersons welcome and opening remarks.
10:15AM
(PDT)
Mohit Goenka
Head of Core Engineering (VP)
Grindr

12:10PM - Day 2
View Panel: Embracing AI to Drive Digital Transformation

10:15AM - Day 1
View Presentation: Building Large Scale Applications

01:20PM - Day 2
View Panel: AI Driven Digital Transformation
Presentation: Building Large Scale Applications
To follow soon …
10:45AM
(PDT)
Ash Damle
Head of AI & Data Science
The Modern Data Company

10:45AM - Day 1
View Presentation: DataOS – The Decision Ops Platform Helping Data Scientists and Engineers Work Faster, Better & Easier

02:30PM - Day 2
View Panel: Data led Intelligent Decision Making
Presentation: DataOS – The Decision Ops Platform Helping Data Scientists and Engineers Work Faster, Better & Easier
Align data strategy with business strategy by transforming a siloed data infrastructure into a modern programmable enterprise.
11:15AM
(PDT)
Mohan Konduri
Director of Engineering
Indeed

11:15AM - Day 1
View Presentation: Reinforcement Learning Strategies in Experimentation

12:00PM - Day 1
View Panel: Making the Most of Data
Presentation: Reinforcement Learning Strategies in Experimentation
A/B testing or Experimentation plays a key role in decision making. Data driven approaches with science underpinnings provide the needed rigor to test hypotheses and make decisions. There are however a class of decisions where variable assignments based on Reinforcement Learning techniques make some tests feasible and add velocity (shorter experimentation duration) to others. These strategies don’t conform to the standard hypothesis testing template but serve the same end goal of data driven decision making. We will go through an overview of multi-arm bandits and bayesian parameter tuning as RL strategies applied to experimentation systems.
11:45AM
Networking Break
12:00PM
(PDT)
Aneel Kumar
Senior Director, Product & Platform Engineering Services
Accenture

10:00AM - Day 2
View Applied Data & Analytics: Chairpersons Welcome
Zachary Van Doren
Senior Director, ISV Alliances
ActionIQ

12:00PM - Day 1
View Panel: Making the Most of Data
Josh Meurer
National Data & AI Practice Director
Insight

12:00PM - Day 1
View Panel: Making the Most of Data
Mary MacCarthy
Data Advocate
Hightouch

12:00PM - Day 1
View Panel: Making the Most of Data

10:35AM - Day 2
View Keynote Presentation: If you’re Stopping at Analytics, you’re letting your Data Die
Lewis Mbae
Head of Customer Engineering
RudderStack

12:00PM - Day 1
View Panel: Making the Most of Data
Mohan Konduri
Director of Engineering
Indeed

11:15AM - Day 1
View Presentation: Reinforcement Learning Strategies in Experimentation

12:00PM - Day 1
View Panel: Making the Most of Data
Michael van Meurer
Senior Solutions Engineer
Kili Technology

12:00PM - Day 1
View Panel: Making the Most of Data
Panel: Making the Most of Data
- Identifying and breaking down silos across departments and business data stacks.
- How to maximise data sets and data pipelines.
- Aligning data with specific business goals – making use of insights for targeted business e.g. seasonal buying cycles and customer demand.
12:50PM
(PDT)
Ben Tonon
Enterprise Account Executive
Metric Insights

12:50PM - Day 1
View Presentation: Universal BI Portal: The Missing Ingredient to your BI Strategy
Presentation: Universal BI Portal: The Missing Ingredient to your BI Strategy
Governance can be intimidating for many large enterprises. Users have access to multiple tools and content, and establishing a uniform layer of governance on top of all your BI, Big Data, and Analytics tools is a daunting task. However, governance is critical, and the lack of proper governance leads to poor user engagement and low ROI from BI, big data, and AI initiatives.
Join this session to learn how you can…..
1. Establish a unified portal to provide a single source of truth for data insights
2. A Governance layer that provides analysts a way of documenting, categorizing, and certifying key BI reports and publishing them
3. Track usage and feedback of your analytics
01:10PM
Lunch & Networking Break
01:40PM
(PDT)
Gil Levonai
CMO
Vanti

01:40PM - Day 1
View Presentation: Accelerating AI Deployment in Manufacturing and Achieving Tangible ROI within days!
Presentation: Accelerating AI Deployment in Manufacturing and Achieving Tangible ROI within days!
AI in manufacturing is a hot topic around the industry, with multiple potential use cases, vendors, and methodologies.
The challenge that manufacturers face is that the path from concept to deployment to ROI is very resource and time-consuming, requiring months of work and multiple expertise. And in many cases, the ROI is never actually achieved.
In this session, we will explore the regular path from concept to ROI in manufacturing AI projects and how new technologies can shorten it to days instead of months.
We will showcase a real-life case study involving early fault detection model deployment in one week that resulted in substantial savings and efficiencies.
02:00PM
(PDT)
Pranay Chandur
Associate Director, Data Science
Walmart

02:00PM - Day 1
View Presentation: Back to Basics – Creating a Strong Business Data Strategy

02:30PM - Day 2
View Panel: Data led Intelligent Decision Making
Presentation: Back to Basics – Creating a Strong Business Data Strategy
- Understanding the challenges businesses are facing and looking at how data can be the answer – not a one size fits all response.
- Utilising the enterprises strategic advantage – how to unlock data’s value.
- Studying current processes for capturing data and looking at next steps.
02:20PM
(PDT)
Cal Al-Dhubaib
CEO, AI Strategist
Pandata

02:20PM - Day 1
View Presentation: Generating Business Value with Applied Machine Learning and AI
Presentation: Generating Business Value with Applied Machine Learning and AI
The what: While AI continues to evolve at a rapid pace – adoption rates growing day over day – projects still fail at a disappointingly high rate. The why: In the past, capturing data at scale and building models was the challenge, but today we’re confronted with the issue of making AI more robust while avoiding the risk of unintended consequences. While the tools are new, many challenges remain the same. This session will cover:
- Building blocks to develop requirements for AI-driven projects
- Examples of identifying and mitigating project risks and unintended consequences
- How to build the business case for an AI project (and get buy in)
02:40PM
(PDT)
Wing Au
Member of the Research Staff in the Discovery Intelligence team
Fujitsu

02:40PM - Day 1
View VIRTUAL PRESENTATION: Understanding the Data Eco-System with Discovery AI

02:40PM - Day 1
View Presentation: Understanding the Data Eco-System with Discovery AI
Presentation: Understanding the Data Eco-System with Discovery AI
- Data Eco-System – From Tabular & Object Data to Graph Data
- Graph Data in Industrial Applications
- Fujitsu and Larus Partnership – From Graph Database to Graph AI
- Explainable Graph AI (GXAI) with EnsemBiz – Deep Tensor
- Deep Dive Example into Discovery GXAI Pipeline
03:00PM
Networking Break
03:30PM
(PDT)
Jascha Prosiegel
Market Lead North America, Artificial Intelligence Risks
Munich Reinsurance

03:30PM - Day 1
View Presentation: Financial Risk Management of B2B AI
Presentation: Financial Risk Management of B2B AI
- Instruments to manage risks between AI vendors and buyers.
- Case studies of product differentiation through guarantees by AI vendors.
- Outlook on technology risk transfer enabling the AI transformation
04:00PM
(PDT)
Raj Joseph
CEO & Founder
DQ Labs

04:00PM - Day 1
View Presentation: Delivering the Data that Matters
Presentation: Delivering the Data that Matters
To follow soon …
04:10PM
(PDT)
Kunal Agarwal
Co-founder and CEO
Unravel Data

04:10PM - Day 1
View Presentation: Empowering Data Teams with DataOps Observability
Presentation: Empowering Data Teams with DataOps Observability
- Why data teams require an observability platform designed specifically for data applications.
- What multidimensional DataOps observability helps manage (performance, cost, data quality).
- How DataOps observability isn’t just for engineers or operations but empowers different data team members across the DataOps lifecycle.
04:30PM
(PDT)
Matt Linder
Senior Machine Learning Engineer
Headspace

04:30PM - Day 1
View Presentation: Mindful AI at Headspace – From Impersonal Statistical Modeling to Personalized Care

03:30PM - Day 1
View Presentation: Mindful AI at Headspace – From Impersonal Statistical Modeling to Personalized Care
Presentation: Mindful AI at Headspace – From Impersonal Statistical Modeling to Personalized Care
Headspace is a values-first company: through 10 years of innovating the use of technology in meditation and mindfulness, the focus has never shifted from making sure that our approach to technological implementation is as mindful as our content.
Over the last year, much of that innovation has centered around ML-powered personalization: from in-app content recommendation to push notifications to AI-driven dynamic welcome flows. But implementing ML/AI solutions brings unique challenges: personalization is inherently intimate and demands great sensitivity in the ways we use and communicate member data.
In this talk, we’ll explore how Headspace balances the intimate and data-centric process of building ML solutions while maintaining our brand identity as a mindful actor.
Pre-recorded session
05:00PM
(PDT)
End of Day 1
View Day 2 content here:
Data Optimisation | Big Data | Intelligent Decision Making | Data Storage | Industry Use-cases
Personalisation | Edge AI | Digital Transformation | Future Progressions | Industry Use-case