June 10 - 11, 2020




DATAx San Francisco is a cross-industry event for business leaders, strategists, and practitioners looking for best practices and strategic insights to help increase business growth and gain marketplace advantage.

DATAx provides a unique blend of data-focused content tailored to help you find real-world solutions to common challenges.

Our program is specifically curated to examine the most relevant topics on the minds of data scientists and business decision-makers. With an emphasis on collaboration, DATAx is the event where the technical and strategic conversations that change business models are started.

Save $500 when you register before February 29. Team discounts are available up to 50% off. Please email enquiry@argyleforum.com for details. [REGISTER NOW]




What to Expect at DATAx SF 2020

Conference Topics

Strategy and Leadership, Artificial Intelligence, Machine Learning, Deep Learning, Structured and Unstructured Data, Data Driven Culture, Data Governance, Computer Vision, Data Visualization, Natural Language Processing, Data Personalization, Neural Networks, Cryptographic Algorithms, Blockchain, IoT, Customer and Marketing Analytics, Robotics

Interested in speaking? Please submit your complete abstract to Show Producer Sherry Robinson srobinson@argyleforum.com.

Audience Details

Our audience will be 400+ business leaders, strategists, and practitioners looking for insights, collaboration, and solutions on how to utilize data to make informed business decisions.


Bring back actionable insight by participating in two days of candid talks and round tables.

Collaborate with peers in the interactive DATAx Labs. Choose from a series of workshops to fit your business needs and personal goals.


Connect with 400+ data leaders across all industries and experience levels to expand your network.

Meet the disruptive startups and innovators who are changing the world.


Discover cutting-edge tools and techniques.

Immerse yourself in automation, data, and mobile technologies that will unleash your potential.

4 Tracks To Choose From

TRACK 1 – Strategy & Leadership in the Age of Data Dominance

TRACK 2 – Data Science & Artificial Intelligence Working Together

TRACK 3 – Data Utilization: The Art of Extracting Valuable Insights

TRACK 4 – Workshops


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Day 1 Wednesday 10th















Starting at 7am

7:30am – 8:30am

Networking Breakfast

Starting at 8am

8:30am – 8:45am

Opening Remarks

8:45am – 9:15am

Does Your Data Team Play Well with Others?

How data interacts with other business functions varies from company to company. Organizational structure plays a significant role on the impact data can have on your organization. As titles change and evolve so must the roles and responsibilities to suite changes in business goals. Hear first-hand how leading Chief Data Officers are structuring strong data teams. In this session, topics of discussion will include: ▪ Organizational structure ▪ Evolution of roles and responsibilities ▪ How data science works across functions

Starting at 9am

9:15am – 10am

KEYNOTE ADDRESS: Bringing Your Data Together: Creating a Holistic View of Your Customer

You literally have data everywhere, but how do you bring it all together to create a holistic view of your customer? The struggle is real! Your company is not the only one drowning in a sea of unconnected data. Hear how companies are solving navigating the data lakes to bring data together and extract valuable insights. In this session, topics of discussion will include: ▪ Creating a holistic customer profile ▪ Systems integration ▪ Cross functional data teams

Starting at 10am

10am – 10:45am

Morning Networking Break & Expo Round Robin Challenge

10:45am – 11:15am

PANEL DISCUSSION: Preserving the Virtue of Your Data – (Track 1)

Do not assume that everyone in your company values data in the same way. Each department has its own unique relationship with data. Implementing clear processes around data is the only way to safeguard your company’s most valuable asset. In this session, topics of discussion will include ▪ Incorporating data governance into your business strategy ▪ Developing a culture of data citizens ▪ Processes for preserving data quality

10:45am – 11:15am

USE CASE: Demystifying Applied ML – Building Frameworks & Teams to Operationalize ML at scale – (Track 2)

Comprehending how to match the deep knowledge of a subject matter expert to the technical application of ML programs remains a major barrier to applied ML in the workplace. Join us as we examine best practices on how to scale operationalizing ML to solve complex problems. In this session, topics of discussion will include: ▪ Outlining your business Objectives: defining goals and success criteria. ▪ Providing the right technology and tools ▪ Structuring and training your teams

Dr. Nels Lindahl Director, Clinical Decision Systems
CVS Health

10:45am – 11:15am

USE CASE: How Strava is Using Data Visualization to Fuel Growth – (Track 3)

The Strava dataset grows by millions of activities a day and comprises trillions of GPS data points; this quantity of data is gold for businesses. Discover how user data at Strava is transformed into innovative visualizations of human performance: heatmaps, fitness stats, mobile routes, and even urban planning/mobility. Hear first-hand how they are able to scale visualizations, and detail how data sets are analyzed and transformed into business insights the company uses to fuel its growth. In this session, topics of discussion will include: ▪ How to effectively scale visualization ▪ Using Data Visualization for increase growth ▪ Extracting quality data from large datasets

Cathy Tanimura Senior Director, Analytics & Data Science

10:45am – 12:25pm

WORKSHOP: Moving from Raw to Relevance in Real Time – (Track 4)

Abstract soon to come! Hosted by Micro Focus

Theresa Melvin Chief Architect, AI-Driven Big Data Solutions
Hewlett Packard Enterprise

Starting at 11am

11:20am – 11:50am

Self Service Enablement – Empowering Data Discoveries Across the Organization – (Track 1)

Achieving the level of a data driven organization opens up a new world of possibilities for your organization. With a stable data governance strategy in place and a workforce fluent in data you are able to empower your workforce to drive data focused initiatives across the organization. In this session, topics of discussion will include: ▪ Defining your data governance strategy ▪ Establishing a level of data fluency within your organization ▪ Training on the tools and techniques required to effectively analyze data

11:20am – 11:50am

How to Effectively Accelerate ROI on Your AI Investments – (Track 2)

Every organization wants to use data as its core advantage, but struggle with scaling and accelerating their data initiatives. Many of the challenges can be attributed to the fact that the data, and its applications are advancing faster than the technologies used to process and design them. Join us as we dive into the root cause of many common data challenges and incorporate applied patterns to solve them. In this session, topics of discussion will include: ▪ How to design efficient data models that will enhance the performance of your AI/ML tools. ▪ How to successfully use applied patterns to address the root cause of your data challenges ▪ Real-World solutions to scale and accelerate AI/ML processes

Ronak Shah Head of Data Engineering

11:20am – 11:50am

PANEL DISCUSSION: Dirty Data – Strategies for Improving the Quality of Your Data – (Track 3)

Are you confident in your organizations data? If the answer is NO, then you have a major problem. High quality data can increase business performance for your organization and validate key business decisions Learn best practices for protecting the quality of your data. In this session, topics of discussion will include: ▪ Increasing business performance ▪ Improving data quality ▪ Protecting our data

11:55am – 12:25pm

USE CASE: Business Strategies to Burst the Bias Bubble – (Track 1)

Collaborative decision making under uncertainty happens daily in business. Machine learning obscures bias behind the complexity of its algorithms. Bias is corrosive because it hides in metrics and the systems we use to make decisions every day. It gives us false confidence that our decisions are data driven when in reality, they are bias driven. Even data scientists often don’t understand the data and models well enough to prevent biased outcomes. Autonomous cars are 5% more likely to hit PoC because their training data wasn’t diverse enough. Amazon abandoned their automated candidate screening system because it was biased against protected classes. Join us as we dive into what you can do to control bias within your organization. In this session, topics of discussion will include: ▪ Creating a culture that strives to reduce bias ▪ Using Machine Learning systems to reduce uncertainty ▪ Reducing uncertainty around key decisions by controlling bias

Vin Vashishta Data Scientist, Strategist, Author
V2 Machine Learning Consulting

11:55am – 12:25pm

PANEL DISCUSSION: Powering Data with Cutting Edge Technology – (Track 2)

We all know that there is no shortage of data, but collecting, cleaning and extracting relevant insights is a big problem that many companies struggle with. In this session, topics of discussion will include: ▪ The future of the stack ▪ Budgeting for your company’s future. ▪ How to source the best technology for your business

11:55am – 12:25pm

Using Natural Language Processing to Obtain Valuable Insights – (Track 3)

Many industries are employing natural language processing techniques to aid with recognizing trends and industry predications. These techniques have enabled some companies to solve common business challenges and also reveal new opportunities for company growth. Join us to learn effective natural language processing approaches. In this session, topics of discussion will include: ▪ Organizing information according to context ▪ Preparing your data ▪ Predicting lifetime customer/user value

Starting at 12pm

12:30pm – 1pm

AI + Humans Working Together to Drive Revenue – (Track 1)

When it comes to AI collaboration is key. The fear that humans will be replaced by the machines is still very prevalent in the workforce. The reality is AI is a tool and humans will always be needed to manage the tools. Data leaders must spearhead the change in mindset around the implementation of AI. Working together machines will provide the consistency and speed to uncover patterns in real-time and humans will provide the logic to extract insights that will help companies make better informed decisions. In this session, topics of discussion will include: Fear of the machines ▪ Scaling AI across an organization ▪ Upskilling your workforce

12:30pm – 1pm

PANEL DISCUSSION: Communicating Value to Your Internal Stakeholders – (Track 2)

The realm of data and AI is still very new and evolving daily. Practitioners are constantly challenged with staying abreast of new technology, regulations and how it all affects the company. In this session we will address effective ways to communicate the value of data & AI to internal stake holders. In this session, topics of discussion will include: ▪ Technology advances ▪ GDPR & CCPA and the effect on data ▪ Winning stakeholder buy-in

12:30pm – 1pm

Creating Game Changing Algorithms to Gain a Competitive Advantage – (Track 3)

Algorithms have allowed companies like Uber and Stitch Fix to disrupt industries and change the way consumers spend their time and money. Many data teams struggle to develop smart algorithms that deliver game changing actionable insights. Discover the methodology that goes into creating algorithms that can significantly impact your business. In this session, topics of discussion will include: ▪ Finding relevant data sources ▪ Testing and validation ▪ Identifying relevant business objectives

Starting at 1pm

1pm – 2pm

Networking Lunch

Starting at 2pm

2pm – 2:30pm

USE CASE: Getting Your Data House in Order: Critical Issues in Advancing Data Governance – (Track 1)

Data is the asset of the present – and the future. Whether it’s generating insights, driving innovative product development or improving decision making, the need for and dependence on big data has never been greater. Data is a critical strategic asset for any company looking to leverage the power of AI, machine learning, and other advanced analytics. However, for companies that were not “data-first,” implementing a data governance program that both maximizes the quality of their data and addresses the obligations created by the changing regulatory landscape remains a challenge. This session will explore the critical legal and practical issues a business must consider as it develops and implement compliant and effective data programs. In this session, topics of discussion will include: ▪ How to structure a data governance program that addresses their current regulatory obligations to comply with new privacy and security obligations ▪ Best practices in creating a data-focused business culture ▪ Real-world examples of trends, challenges, opportunities and developments to come in data collection and use

Jessica B. Lee Partner, Cp-Chair, Privacy, Security & Data Innovations
Loeb & Loeb

2pm – 2:30pm

PANEL DISCUSSION: Is AI the Right Fit for Your Business? – (Track 2)

There is still a lack of understanding of how AI & ML should be used within organizations. Many companies have spent considerable amounts of money (blown budgets) on AI/ML technology and have not seen any ROI on these investments. Leaders are tasked with sourcing new technology, but they need to know that the technology is the best fit for the business. This session will help you manage your expectations around AI/ML and provide you with realistic goals for how AI/ML can fit your business objectives. In this session, topics of discussion will include: ▪ AI on a shoestring budget ▪ Sizing AI to fit your business ▪ Managing stakeholder expectations around AI

2pm – 2:30pm

The Value is in the Details – (Track 3)

When it comes to obtaining the best insights from your data the value is often hidden in the minor details. Data collection is only the beginning of the data journey; your data is useless if it is incomplete or queries aren’t structured properly. Learn the varies methods companies are using to uncover the valuable nuggets of information that their data holds. In this session, topics of discussion will include ▪ Importance of Data integrity ▪ How to effectively structure your data ▪ Best Practice for uncovering value in your data

2pm – 3:30pm

Data Visualization – (Track 4)

In this immersive workshop you will get hands on training on some of the latest tools in data visualization. Learn how to transform data into knowledge that is relevant for decision making. Topics of discussion will include: ▪ Visual Data Storytelling ▪ Which tools are most effective for your industry? ▪ Extracting the most relevant information to showcase

2:30pm – 3pm

USE CASE: A Guide to Building a Data Driven Culture – (Track 1)

When it comes down to it, organizations struggle with becoming data driven and making it a part of their culture. Hiring a team of data scientists does not fix this problem outright. Success is dependent upon building the right processes, democratizing data and resetting the mentality across the organization. These problems are often more difficult to solve than the tech and math related to data science. Join us in the discussion of a how to guide for building a data driven culture. In this session, topics of discussion will include: ▪ Understand the data maturity model and where to start. ▪ Get an overview of processes and people requirements to drive a data driven culture. ▪ Understand the citizen data scientist movement and the realistic expectations of people outside of data science

Daniel Gremmell Vice President, Data Science

2:30pm – 3pm

PANEL DISCUSSION: Deploying Machine Learning in the Wild – (Track 2)

Join in on this discussion as representatives from some of today’s leading-edge company’s share how they are developing and deploying ML applications with success. Hear the backstories behind the journey; pitfalls, abandoned projects, small wins and successful processes that worked. In this session, topics of discussion will include: ▪ Managing stakeholder’s expectations when developing machine learning ▪ Structuring your team for effective ML implementation ▪ Preparing your data for algorithm training – Do you know what problems you want to solve?

2:30pm – 3pm

USE CASE: The Intuition Behind Machine Learning in Marketing – (Track 3)

Since the year 2013 important breakthroughs and advances in technology have made it possible to run sophisticated predictive models capable of classifying images, text, and sound. Technology has brought to reality self-driving cars, chat bots and a host of other AI powered devices. In this session we will present key insights that will help you make AI/ML more beneficial to your marketing efforts. Through real world case studies, the session will demystify the core technologies around ML and illustrate how to successfully apply the technology. In this session, topics of discussion will include: ▪ How to think and interpret predictive models ▪ What metrics we use to evaluate models ▪ Specific case studies in optimization, channel attribution

Mario A. Vinasco Director BI and Analytics
Credit Sesame

Starting at 3pm

3pm – 3:30pm

PANEL DISCUSSION: Systems Integration – Getting Your Systems to Work in Harmony – (Track 1)

As companies grow so does the technology used to support them; with that growth comes a myriad of systems implementation. Many companies are currently struggling with getting their systems to communication. This lack of communication has made it challenging to easily access all aspects of captured data. Discover real-world examples of how some companies are navigating this communication roadblock. In this session, topics of discussion will include: ▪ Navigating system integration ▪ Growth and technology ▪ Digital transformation

3pm – 3:30pm

USE CASE: Using ML and AI to Produce Real-Time, Scalable, Informed Decisions – (Track 2)

The ability of ML and AI to provide real-time, scalable decision-making support to executive strategy is changing the business landscape. In the healthcare sector, patient privacy, data interoperability, and high stakes patient health ramifications intertwine to create a challenging environment in which to use advanced computation techniques. Join us to learn how Johns Hopkins Healthcare’s model, Callisto has been instrumental in predicting suitable health management programs for THEIR patients that deliver concrete return on the overall health of the patient. In this session, topics of discussion will include: ▪ The unique challenges within the healthcare sector that other industries can benefit by understanding ▪ How the runaway cost structures can be fundamentally inverted by targeting pain points with focused ML/AI ▪ How advancements in AI has allowed the healthcare sector to leapfrog into the 21st century as a fully-integrated player in the cyber community

Romy Hussain Director of Healthcare Economics and Data Science
Johns Hopkins Healthcare

3pm – 3:30pm

USE CASE: Streaming (Real Time) Analytics – (Track 3)

Join us as we unbox how TD Banks is taking advantage of streaming analytics in real time. Through real world case studies, you’ll learn how they are using this quick time sensitive process as a competitive edge. In this session, topics of discussion will include: ▪ Five Levels of Streaming Analytics Maturity ▪ Advantages and Disadvantages of streaming analytics in real time ▪ Supportive open source technology

Bharti Bhardwaj Delivery Director
TD Bank

3:30pm – 4pm

Afternoon Networking Break

Starting at 4pm

4pm – 4:30pm

USE CASE: How to Build a Successful Customer Engagement Strategy Using Customer Data

Join us to hear real-world demonstrations and client perspectives on how BRP is utilizing data to better inform its decisions and engagement. BRP has built a lifetime value model to better address customer needs, created a predictive repurchase model and is currently building a new digital team to implement a complete marketing technology solution that will automate & personalize large-scale messages to the right consumers at the right time. In this session, topics of discussion will include: ▪ How to effectively personalize large-scale messages ▪ Creating models to improve lifetime customer value ▪ Building teams to support data initiatives

Dan Sorotschynski Vice President, Global Brand Strategy & Consumer Engagement

4:30pm – 5pm

PANEL DISCUSSION: Addressing Bias in AI: How “Woke” Are Your Algorithms?

Data leaders are acutely aware of bias in data collection and they are wrestling with effective ways to ensure that their data processes are bias free. Join us for a conversation about bias and how leaders are navigating this major data quality issue. In this session, topics of discussion will include: ▪ Reducing bias in machine learning ▪ How to handle explainability ▪ Data governance

Melissa Steach PhD, Workplace Wellbeing Knowledge Lead
Herman Miller

Starting at 5pm

5pm – 6pm

Networking Cocktail Reception

Who attends our events

We bring the world’s data community together


San Francisco Marriott Marquis

Venue & Hotel Block Info

SAN FRANCISCO MARRIOTT MARQUIS | 780 Mission Street San Francisco, CA 94103


Whether you are in town for business or leisure, San Francisco Marriott Marquis welcomes travelers to Northern California with exceptional service, spacious hotel rooms and suites and a prime downtown location. From our towering hotel, guests have easy access to numerous attractions, including Oracle Park, the Moscone Center and the sights of SoMa. Inside, you can relax and recharge in contemporary rooms and suites that enjoy impressive views of the city.


We have negotiated a discount rate of $359 per night for DATAx attendees at the San Francisco Marriott Marquis. You can book in the event room block using this link.





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