Conference Program

Data Summit 2022 is a unique conference that brings together IT practitioners and business stakeholders from all types of organizations. Featuring workshops, panel discussions, and provocative talks attendees get a comprehensive educational experience designed to guide them through all of today’s key issues in data management and analysis. Whether your interests lie in the technical possibilities and challenges of new and emerging technologies or using Big Data for business intelligence, analytics, and other business strategies, we have something for you!

Access to all tracks including AI & Machine Learning Summit, DataOps Boot Camp, and Database & DevOps Boot Camp is included when you register for an All-Access Pass or Full Two-Day Conference Pass. Attendees may switch between tracks as they choose. Only interested in the two-day AI & Machine Learning Summit or our one-day Boot Camps? Stand-alone registration for these events is also available.

Click here to view the Final Program [PDF].

 

Monday, May 16

Preconference Workshops

 

W1. Essentials of Data Privacy and Security

09:00 AM2022-05-162022-05-16

Monday, May 16: 9:00 a.m. - 12:00 p.m.

This is an introduction, overview, and update for professionals who interact with data privacy functions and want to understand privacy and data security better. We walk through not just the regulatory environment and the ways in which businesses are responding (and failing to respond), but why privacy is important and what's changed to make that so relevant today. Learn about fair information practices, the legislative landscape, and how businesses can best secure their data. Don't get caught short when it comes to protecting the data stored by your organization. Join privacy professional Jeff Jockisch in this interactive workshop to understand how to better protect the sensitive data in your business.

Speaker:

, CEO, CIPP/US, PrivacyPlan and Data Collaboration Alliance

 

W2. Introduction to Knowledge Graphs

09:00 AM2022-05-162022-05-16

Monday, May 16: 9:00 a.m. - 12:00 p.m.

Knowledge graphs are a valuable tool that organizations can use to manage the vast amounts of data they collect, store, and analyze. Enterprise knowledge graphs’ representation of an organization’s content and data creates a model that integrates structured and unstructured data. Knowledge graphs have semantic and intelligent qualities to make them “smart.” Attend this workshop to learn what a knowledge graph is, how it is implemented, and how it can be used to increase the value of your data. This is a very interactive workshop, so be prepared not only to learn about knowledge graphs but to actually build one.

Speakers:

, COO, Enterprise Knowledge LLC

, Senior Consultant, Data and Information Management, Enterprise Knowledge, LLC

 

W3. Basics of Machine Learning

01:00 PM2022-05-162022-05-16

Monday, May 16: 1:00 p.m. - 4:00 p.m.

Machine learning is revolutionizing the process of complex decision-making by enabling the analysis of bigger, more complex datasets and the delivery of faster, more accurate results. Although the technology is developing rapidly, many projects are still in their early phases while other have hit a wall because they can’t keep up with the volume and variety of data. From selecting data sets and data platforms, to architecting and optimizing data pipelines, to evaluating commercial and open source frameworks, there are many success factors to keep in mind. Most ML models are trained over examples collected at different points in time, and often are trained to predict the future. Machine learning needs the ability to forget — to learn what’s relevant now. Attend this workshop to learn how to iterate on ML models with event-based data, and develop scalable, real-world machine learning pipelines and applications.

Speaker:

, VP of Product, Kaskada

 

W4. Build Actionable Road Maps for Enterprise Data and Analytics

01:00 PM2022-05-162022-05-16

Monday, May 16: 1:00 p.m. - 4:00 p.m.

The starting point in developing and launching an enterprise data and analytics strategy is to understand the interrelationships that are necessary to deliver analytics capabilities. These relationships also account for skills and roles of everyone who works with data, from business executives to business analysts to data scientists. To measure and drive success, an actionable road map is needed, with each phase focused on being lean with a business impact. Attend this workshop to learn how to designate business drivers into analytic capabilities and data priorities, create and implement a road map, and deliver a compelling executive briefing.

Speaker:

, President, Eckerson Group

Tuesday, May 17

Keynote

Moderator:
Marydee Ojala, Editor-in-Chief, Online Searcher Magazine, USA
 

Welcome & Opening Keynote: Data Is Not the New Oil

09:00 AM2022-05-172022-05-17

Tuesday, May 17: 9:00 a.m. - 9:45 a.m.

Sharing insights from his bestselling book, Infonomics, Laney discusses why information both is and is not an asset. He covers issues around information ownership, rights, and privileges; explores how best to monetize assets and measure realized value; and explains his set of generally accepted information principles culled from other asset management disciplines. Learn why he believes we should stop talking about data as the new oil and concentrate on acting on its true importance.

Speaker:

, Data & Analytics Strategy Innovation Fellow, West Monroe and Author of "Infonomics", visiting professor at University of Illinois Gies College of Business

 

How to Choose: Data Lake, Lakehouse, or Mesh?

09:45 AM2022-05-172022-05-17

Tuesday, May 17: 9:45 a.m. - 10:00 a.m.

When it comes to data analytics infrastructure, there are a wealth of options for storing and querying information. New technological approaches allow for more flexibility in cloud data management and are democratizing data for use across the organization. By stripping away data engineering complexity and lowering total cost of infrastructure ownership and maintenance, more and more organizations are unlocking the value of analytics at scale. Join Thomas Hazel as he dives into the latest and demystifies them, so you can determine which is right for your organization. Sponsored by Chaos Search. 

Speaker:

, Founder/CTO, ChaosSearch

 

Tuesday, May 17

Track A: Modern Data Strategy Essentials Today

Modern Data Strategy Essentials Today is your guide to the key principles data-driven companies are applying to achieve success in our increasingly complex world of data sources, types, applications, requirements, and user expectations. Attend this track to learn how to align technology, people, and processes with the complete data journey and the capabilities that support your current and future needs.

Designed for chief information officers, chief data officers, digital transformation leaders, IT business liaisons, enterprise architects, data architects, data engineers, data management and analytics professionals.

 

A101. Embracing Digital Transformation

10:45 AM2022-05-172022-05-17

Tuesday, May 17: 10:45 a.m. - 11:45 a.m.

Digital transformation efforts today are targeted not only at how data is managed and stored, but also at how it is leveraged to deliver insights and competitive advantage to businesses across a range of industries.

Consciously Transforming Your Enterprise

To transform your organization, it is essential to have management support. The insurance industry is changing rapidly due to changing customer expectations of digitally enhanced and tailored interactions with insurers as well as the emergence of tech-savvy new entrants into the space that are building the types of experiences customers are seeking. Learn how Arbella proposed and crafted a solution that addressed immediate concerns and showed its relevance to meeting the challenges of the envisioned future.

Speakers:

, Head, Innovation & Data Science, Arbella Insurance Group

, Commercial Lines Underwriting Manager, Arbella Insurance Group

Data-Driven: Don't Run Before You Can Walk

The pandemic has accelerated the digital transformation journey for many organizations, regardless of maturity and readiness. As they continue to face an explosion of data, organizations need to be very thoughtful in utilizing data for its intended use. According to various analyst research, many data management programs fail in the first 3–6 months. Why does this happen? Often, it is due to readiness. Organizations are not prepared to tackle the full data management program. One tactic that can help is to break up a project into smaller chunks so that you learn to walk before running.

Speaker:

, VP & Business Segment Manager - Data Management Solutions, Dun & Bradstreet

 

A102. Succeeding With Data Projects in the Real World

12:00 PM2022-05-172022-05-17

Tuesday, May 17: 12:00 p.m. - 12:45 p.m.

Data projects that are completed on time, address changing requirements, and deliver value in the real world require a combination of skills and technologies, as well as the right people.

How to Create and Sustain a High-Performing Remote Data Team

Team management in data careers is a balancing act between providing the support and clarity that team members need to get the job done and keeping them engaged to create innovative solutions and improve on existing ones. This interactive session offers 10 strategies for building and sustaining high-performing data teams that draw from lessons learned on the job as a data professional.

Speaker:

, Corporate Manager Database Operations, Baptist Health South Florida

Accelerating the Move to the Cloud with Real-time Connectivity

Lam describes Office Depot's journey from a legacy data warehouse to the cloud, including how real-time standards-based connectivity allowed Office Depot to immediately leverage existing analytics tools and processes without having to rebuild its infrastructure or disrupt its business during this move.

Speaker:

, VP Marketing & Strategy, CData

 

A103. Streamlining Your Approach to Data

02:00 PM2022-05-172022-05-17

Tuesday, May 17: 2:00 p.m. - 2:45 p.m.

Data professionals have a wide array of choices to help them deal with the growth and diversity of their data. But with so many technology options that can be deployed on-prem, in the cloud, or a combination thereof, the complexity is also increasing.

Unwieldy Tech While Developing a Common Strategy:How the CIO of a P&C Insurance Company Tackled Its Data Strategy

The CIO for one of the 25 largest property and casualty insurance companies in the world was faced with the challenge of its business units running their business intelligence and analytics reporting on an ever-growing number of disparate tools and systems. From Informatica to Business Objects, SAS to Power BI, OBIEE to Hadoop, the multinational company needed a way to not only reduce its costs in managing these disparate tool sets but also sought to develop an integrated data strategy that would align the business units with one source of the truth and lead the company into the future. Sasso discusses the challenges of running the business currently on the myriad of tools while planning the data strategy for the future and the road map to get to that strategy.

Speakers:

, VP, Data Management, Datavail

, Former VP, Deputy Chief Information Officer (CIO), Property & Casualty Insurance Company

 

A104. Becoming an Insights-Driven Enterprise

03:15 PM2022-05-172022-05-17

Tuesday, May 17: 3:15 p.m. - 4:00 p.m.

The ability to quickly act on information to solve problems or create value has long been the goal of many businesses. However, it was not until recently when new technologies emerged that the speed and scalability requirements of high quality analytics could be addressed both technically and cost-effectively by organizations on a large scale.

Gaining Insights From Clickstream Data

Wayfair’s massive, petabyte scale clickstream data environment consists of processes and data sources designed to capture and represent external customer activity while they browse one of our storefront sites/apps. To gain important insights to inform our strategic direction, we process clickstream data sets daily using Google BigQuery. Our intent is to capture all activity from legitimate external customers and to create actionable site data for marketing and storefront analytics. Taking a deep dive into the data processing architecture, Viswanathan discusses methods, technology, and processes used at Wayfair to build data processing and analytics at scale. She showcases the next gen data modeling practices, with special emphasis on how data processing has advanced with the advent of cloud computing.

Speaker:

, Staff Engineer, Wayfair

Unlocking Business Value With Real-time Data Analytics

Real time analytics is the new frontier for data management and analytics. This shifts from focusing on “big data, which tends to be siloed, slow, and looking backwards, to “fast data,” where data is captured and analyzed in real time. Schneider describes how to make “in the moment” business decisions that increase performance and ROI while decreasing costs and failures.

Speaker:

, Chief Marketing Officer, KX

 

A105. Increasing the Time to Value of Data

04:15 PM2022-05-172022-05-17

Tuesday, May 17: 4:15 p.m. - 5:00 p.m.

To turn data into insights and leverage the wealth of information that they are collecting, organizations need to ensure that their data is up-to-date and trustworthy. There is no magic answer. It’s a combination of technology and processes.

Every Problem Is a Data Problem: How Bad Data Is Killing Your Business
Campbell, CEO of Syniti, and Fersht, CEO and chief analyst at HFS Research, discuss data value research conducted with Global 2000 C-level executives. Data investments are poised to accelerate since data is a critical component of digital and other transformation efforts. However, only 5% of the executives surveyed have a high level of confidence in their data. Learn why data is so important to businesses today, how data quality and company success are inextricably linked, and how to close the gap between knowing the value of data and leveraging it effectively.
Speakers:

, CEO, Syniti

, CEO & Chief Analyst, HFS Research

 

Reception in the Data Solutions Showcase

05:00 PM2022-05-172022-05-17

Tuesday, May 17: 5:00 p.m. - 6:00 p.m.

 

Tuesday, May 17

Track B: Emerging Technologies & Trends in Data & Analytics

Moderator:
Dave Skrobela, Managing Manager, Earley Information Science

Emerging Technologies and Trends in Data and Analytics takes you through the most exciting developments reshaping the industry and helping businesses close the data value gap, from the rise of data fabrics to the continued growth of automation technologies, data self-service initiatives, cloud-native analytics, and IoT stream processing projects. Attend this track to dive into innovative new technologies and practices to meet growing challenges and opportunities.

Designed for chief information officers, chief data officers, digital transformation leaders, enterprise architects, data architects, data engineers, data scientists, data management and analytics professionals.

 

B101. Architecting for Speed & Scale

10:45 AM2022-05-172022-05-17

Tuesday, May 17: 10:45 a.m. - 11:45 a.m.

The pressures on organizations keep increasing—to speed up the pace of insights, improve time to market, fine-tune personalization, and create usable products and services. Central to these efforts is a data architecture and design crafted for speed and scale.

Technically Right, Effectively Wrong: How to Avoid Creating the ML or Analytics Application No Customer Wants to Use

Around 85% of analytics, big data, and AI projects will fail, despite massive investments of money. It’s not new news, but it still reflects on how powerfully design affects speed, scale, and usage. Why are customers and employees not engaging with these data products and services? Often, they weren’t designed around user needs, wants, and behavior. A "people first, technology second" approach can minimize the chance of failure and drive your analytics/AI/data/product team to create innovative and indispensable software solutions. Don't be that designer.

Speaker:

, Founder & Principal, Designing for Analytics

Big Data Architecture—Mesh Anyone?

Providing a look at hype versus reality, this presentation offers a data practitioner’s view of the latest and greatest design structure for big data, including the current problems that need to be addressed with data mesh.

Speaker:

, Engineering Lead, Federal Reserve Bank of San Francisco

 

B102. The New World of Data Architectures

12:00 PM2022-05-172022-05-17

Tuesday, May 17: 12:00 p.m. - 12:45 p.m.

From data warehouses to data lakes to data lakehouses, there is a growing array of choices when it comes to data platforms, deployment models, and features. At the same time, many challenges remain the same, including data integration and governance, performance, and management and monitoring.

Data Lakehouse, Data Mesh, & Data Fabric (the Alphabet Soup of Data Architectures)

There are so many new buzzwords lately, including the data lakehouse, data mesh, and data fabric, just to name a few. But what do all these terms mean, and how do they compare to a data warehouse? This presentation covers all of them in detail and explains the pros and cons of each, with suggested use cases so attendees can see what approach will really work best for their big data needs.

Speaker:

, Data & AI solution architect, Microsoft

Accelerate Data Mesh With First-Class Data Products
Data Mesh aims to prescribe that the ownership of data products should live in business domains, ensuring that data is treated as a first-class product across the organization. This is a drastic strategic shift, wherein data is no longer treated as a by-product of activities in which the business engages, but as a key value-driver that should direct business decisions. Learn how to deliver data as a product to empower business domains and become truly data-driven while freeing data teams from costly, time-intensive data management tasks.
Speaker:

, VP of Product, Starburst

 

B103. The Rise of Data Fabrics

02:00 PM2022-05-172022-05-17

Tuesday, May 17: 2:00 p.m. - 2:45 p.m.

Data fabrics are emerging as the most effective means of integrating knowledge throughout the enterprise, and many experts agree that this approach represents the future of enterprise analytics and AI.

Data Architecture Smackdown! Tag teaming Data Fabric, Hub and Mesh for an epic ML and DataOps Battle Royale
With so much data and so many architectural options how do you decide what works for your enterprise without getting a black eye? In the red corner we have the reigning champion “data hub” ready to defend the title. In the blue corner we have the young contender “Data Fabric”, eager to take the top spot. And waiting in the wings is “Data Mesh”, ready to dominate at a moment notice! Who will triumph? Who will fail? Join this presentation to see which approach will reign supreme!
Speaker:

, Director, Product Marketing, Qlik

Weaving Logical Data Fabric Across the Enterprise

The data management world is not standing still; it is constantly evolving as new technologies and new requirements emerge. The need for agility is driving the need for logical, rather than physical architectures. Data ownership has shifted to the domain experts and business teams. The data sharing culture is driving the needs for business oriented data access. We need to empower the analysts, data scientists, and data stewards with real-time trusted data. Let's expand our horizons beyond the traditional integration. Let's talk about the logical approach, let's talk about the Logical Data Fabric.

Speaker:

, Director of Product Management, Denodo

 

B104. Enabling Real-Time Analytics & Big Data Analysis at Scale

03:15 PM2022-05-172022-05-17

Tuesday, May 17: 3:15 p.m. - 4:00 p.m.

Real-time predictive analytics models require a large volume of current, clean, and accurate data pulled from numerous silos to effectively deliver valuable insights. Yet seamless access to multiple data silos is extremely difficult without a real-time, consistent, and secure data layer to deliver the required information to the relevant stakeholders and applications at the right time. 
Enabling Real-Time Analytics With Proactive Data Management

With rapid business change, ongoing market volatility, and enterprise data collection expected to increase at a 42% CAGR over the next 2 years, organizations need to automate manual processes. Proactive data management is key to responding well to unexpected volume and market disturbances. It arms organizations with a single view of accurate, consistent, and trusted real-time data for analytics that can be applied to meet operational and strategic challenges. Fried discusses the traditional patterns that must be re-examined in order to adopt a proactive data management approach that enables real-time analytics.

Speaker:

, Director of Product Management, Intersystems

The Chief Data Officer Analytic Dilemma

In this era of exploding data volumes, CDOs must find the perfect balance between offering a good user experience to analytics experts, having a data pipeline as agile as possible, and keeping the data budget under control. Given the current set of data tools they leverage, this is almost an impossible task. Together let's dive deeper into the CDO's dilemma, and how to solve it. 

Speaker:

, U.S. General Manager, Indexima

 

B105. Achieving Unified Analytics

04:15 PM2022-05-172022-05-17

Tuesday, May 17: 4:15 p.m. - 5:00 p.m.

Different approaches led by various groups within organizations can lead to a sprawling mess, with duplicated effort and wasted opportunities. What’s needed is unified analytics.

Unifying Analytics—Changing Data Architecture to Unite BI & Data Science

The data warehouse has been an analytics workhorse for decades for business intelligence teams. But unprecedented volumes and new types of data, plus the need for advanced analyses, brought on the age of the data lake. Now, many companies have a data lake for data science, a data warehouse for BI, or a mishmash of both—possibly combined with a mandate to go to the cloud. Find out how technical and spiritual unification of the two camps can have a powerful impact on the effectiveness of analytics for the business overall.

Speaker:

, Open Source Relations Manager, Vertica

The Physics of Data
Whether in business or in science, the goal of working with data is always to uncover patterns. Although the rules of quantum mechanics and customer behavior are very different, the techniques needed to move quickly and learn from data are strikingly similar. What is the tradeoff between noise and bias? How can expressiveness aid productivity? What is the most efficient way of communicating data? Plotly CTO and Co-Founder, Alex Johnson, answers these questions by presenting key lessons from his PhD in physics that any organization can use to make smarter use of their data.
Speaker:

, CTO & Co-Founder, Plotly

 

Reception in the Data Solutions Showcase

05:00 PM2022-05-172022-05-17

Tuesday, May 17: 5:00 p.m. - 6:00 p.m.

 

Tuesday, May 17

Track C: Data Ops Boot Camp

Moderator:
Joe McKendrick, Principal Researcher, Unisphere Research, A Division of Information Today, Inc.

Now, more than ever, your company needs agility to navigate today’s rapidly changing business world. Therefore, it’s no surprise that DataOps continues to gain a foothold at enterprises seeking quick, actionable insights. The ability to make better decisions, faster, is a goal shared by many enterprises. At the same time, implementing an effective DataOps program requires significant technology, process, and cultural changes. At DataOps Boot Camp, you’ll hear about key supporting technologies, strategies, real-world success stories, and how to get started on your DataOps journey.

Designed for data scientists, data architects, and data engineers, as well as technology decision-makers and administrators. Both DataOps veterans and novices are welcome.

 

C101. Why You Need DataOps & How to Get Started

10:45 AM2022-05-172022-05-17

Tuesday, May 17: 10:45 a.m. - 11:45 a.m.

Getting started with DataOps doesn’t need to be overly complicated, if you just follow a few basic guidelines.

Building the Business Case for DataOps

DataOps is a must-have for any successful data and analytics team because it is the most effective way to deliver better analytics faster. Increasingly, those companies that neglect to invest in process-driven innovation will be at a competitive disadvantage. But how do you convince other organizational stakeholders to prioritize this important investment today? DataOps supercharges—and does not replace—your existing staff and technology investment. Learn how to build your internal business case and to collect small wins that illustrate DataOps’ impact at your organization.

Speaker:

, CEO and Head Chef, DataKitchen

 

C102. Mastering DataOps Techniques

12:00 PM2022-05-172022-05-17

Tuesday, May 17: 12:00 p.m. - 12:45 p.m.

DataOps is arguably the most powerful data management practice available today for enhancing operational effectiveness. By easing and speeding the exchange of real-time information, it enables improvements throughout the entire value chain, across every industry.

DataOps: Leveraging Learnings From the DevOps Value Chain

Monolithic data supply chains built based on loosely coupled, waterfall-oriented methodologies inevitably end up with pathologically high degrees of inefficiency and poor integration. DataOps aims to fix this. Lugo discusses the techniques of DataOps, their relevance to both data and analytics teams, and their ability to unify architectures in a powerful way. A robust DataOps culture can address challenges through an agile, collaborative, and self-service data marketplace, making it essential for today’s highly data-driven enterprises.

Speaker:

, Director, CTI Data

5 Reasons DataOps Will Fail—And Why It Might Not
Data leaders are using DataOps to modernize their internal practices and increase the value of their data. Are we on the road to El Dorado or more data debt? Join us to hear about the risks of current approaches, and what you can do to increase your chances of success.
Speaker:

, Head of Corporate Strategy, Tamr

 

C103. Overcoming DataOps Challenges

02:00 PM2022-05-172022-05-17

Tuesday, May 17: 2:00 p.m. - 2:45 p.m.

Every technology presents challenges, and DataOps is no exception. But challenges exist to be overcome.

DataOps Is Coming: How Do We Unlock Its Potential?

 Those of us who administer production databases have had to endure significant change relative to how the databases and applications we support are managed. While it isn’t mainstream yet, Data Ops is maturing into a promising automated, process-oriented methodology for higher-quality data extraction and input into your analytics platforms. Hall discusses the impact of DataOps on database professionals, including administrators, and how they can maximize efficiency and performance.

Speaker:

, Senior Solutions Architect, Quest Software

 

C104. DataOps and the Cloud Journey

03:15 PM2022-05-172022-05-17

Tuesday, May 17: 3:15 p.m. - 4:00 p.m.

The cloud is touted as the answer to a multitude of data conundrums, from storage to analytics. It has advantages for DataOps as well.

Exploiting the Multi-Cloud Opportunity With DataOps

Today’s modern, data-driven enterprise is at a crossroads: On the one hand, IT leaders want to take advantage of the flexibility and raw compute power of public cloud services. On the other hand, not all data workloads are created equal, and migrating big data workloads between clouds and on-prem environments can introduce more complexity to an already convoluted process. Agarwal details the common obstacles that data teams encounter in data migration and explains why next-generation data tools must evolve beyond simple observability to provide prescriptive insights, shares best practices for optimizing big data costs, and demonstrates through real-world case studies how a mature DataOps practice can accelerate even the most complex cloud migration projects.

Speaker:

, CEO & Co-Founder, Unravel Data

 

C105. The Future of DataOps

04:15 PM2022-05-172022-05-17

Tuesday, May 17: 4:15 p.m. - 5:00 p.m.

DataOps have many applications in today’s business environment. This panel looks ahead to what the future might bring.

Panelists:

, Associate Professor of Information Systems, Virginia Commonwealth University and Anything Awesome

, CEO, Visible Systems Corporation

 

Reception in the Data Solutions Showcase

05:00 PM2022-05-172022-05-17

Tuesday, May 17: 5:00 p.m. - 6:00 p.m.

 

Tuesday, May 17

Track AI: AI & Machine Learning Summit

Moderator:
Ed Dale, Emerging Technology Associate Director, EY

The adoption of AI and machine learning (ML) technologies has become mainstream at businesses hungry for greater automation and intelligence with innovative use cases spreading across industries. A strong data management foundation is essential to effectively scaling AI and ML programs to deliver repeatable business value. To equip you with the knowledge to succeed, we are bringing together the leading industry experts for a 2-day immersion into real-world deployments, strategies for overcoming common business and technical barriers and key technologies every organization should know about.

Designed for chief information officers, chief data officers, data scientists, data engineers, enterprise architects, data analytics directors/managers, application developers and tech-savvy business leaders.

 

AI101. How to Drive an AI Strategy

10:45 AM2022-05-172022-05-17

Tuesday, May 17: 10:45 a.m. - 11:45 a.m.

Technology without strategy is doomed to fail. Looking at MLOps and Robotic Processes Automation exemplifies the need for clarity and strategic thinking.

Our MLOps Strategy at Galeries Lafayette

Driving the AI strategy in one of the oldest French retailers is a real challenge in and of itself. Using AI to make educated guesses about which customers to target, what products to recommend, and where to display ads is even trickier. Aquarone explains how, as the company’s AI portfolio grew, a standardized canvas to go from a few dozen models to hundreds or even thousands of models became necessary. His team created a set of tools, guidelines, flows, and processes to drive this growth and make sure every prediction is understood, maintained, and used. He details the building blocks of the MLOps Platform and the milestones in transforming the organization to become AI-driven.

Speaker:

, Data Science Products & Innovations Manager, Groupe Galeries Lafayette

Strategies for Unlocking Enterprise Value

For too long, enterprises have lacked the capability to make use of unstructured data. While new technology is the obvious first tool that most organizations look to, savvy automation leaders know that the existing tech stack can be rife with opportunity to yield even more benefit. Wilde identifies ways that enterprises can leverage technology that integrates the existing tech stack to provide a richer, more comprehensive view of enterprise knowledge, while adding structure to their unstructured data. In turn, this strategy unlocks far greater value from existing automation solutions, such as Robotic Process Automation (RPA), and other business-critical technologies, illustrated through use cases in commercial real estate, financial services, insurance, and shared enterprise services.

Speaker:

, CEO, Indico Data

 

AI102. Machine Learning Best Practices Today

12:00 PM2022-05-172022-05-17

Tuesday, May 17: 12:00 p.m. - 12:45 p.m.

Machine learning has evolved considerably over the past few years, and best practices have changed in tandem with that evolution.

How Do I Know My Machine Learning Data Model Is Good?
A data model is the key output part of a machine learning (ML) process. It helps the prediction of new outcomes as new values are inserted into it. But how can we make certain that we have the right data model? Each ML technique is associated with metrics that evaluates the ML data model performance. This presentation uses Oracle Analytics Cloud (OAC) to answer the data model question and demonstrates the most commonly used ML techniques and algorithms, along with their corresponding data model evaluation metric.
Speaker:

, Director Analytics, Datavail

Finally, Realize Business ROI From ML: Unleash Your Event-Based Data

On average, it takes 7 to 18 months, to go from idea to ML model in production. But things are changing. Data platforms are maturing and success is getting within reach of many organizations. Come hear about some top-level trends in machine learning.

Speaker:

, VP of Product, Kaskada

 

AI103. Enhancing AI With Graphs

02:00 PM2022-05-172022-05-17

Tuesday, May 17: 2:00 p.m. - 2:45 p.m.

Graph technology has become a main driver of AI and machine learning advances within a wide variety of industries.

Driving Business Outcomes With Graph Database & AI

The pandemic accelerated the pace of digital transformation across all industries. Organizations are looking for ways to accelerate their analytics, AI, and machine learning projects to increase revenue, manage risks, and improve customer experience. Join us to learn about the three core capabilities necessary to drive the business outcomes: connecting internal and external datasets and pipelines with a distributed graph database, analyzing connected data to discover insights with advanced analytics, and learning from the connected data with in-database machine learning.

Speaker:

, VP, Product & Innovation, TigerGraph

 

AI104. ML Methodologies in the Real World

03:15 PM2022-05-172022-05-17

Tuesday, May 17: 3:15 p.m. - 4:00 p.m.

Theories about machine learning have their place, but applying methodologies to real-world issues give practitioners a leg up.

Application of Advanced Analytics in Anti-Money Laundering

Money laundering impacts society in a number of ways. Banks must adhere to regulatory guidelines to counter them. To combat money laundering, banks use data analytics to gain a complete understanding of transactions data accuracy, completeness, and timeliness from various sources within the bank. Maheshwari explains how extraction, transformation, and loading of data from various systems are critical. Machine learning methodologies are also critical to determine how these transactions (which are millions of dollars on a given day) can be analyzed for any money-laundering activity.

Speaker:

, VP, New York Community Bank

 

AI105. Data Privacy in the Digital Era

04:15 PM2022-05-172022-05-17

Tuesday, May 17: 4:15 p.m. - 5:00 p.m.

Addressing Data Privacy in AI & Machine Learning Projects

In this session, Hodeghatta addresses the challenges of protecting data while providing data for AI and machine learning projects and why data privacy is a concern and can be a hindrance for these types of projects.

Speaker:

, Professor, College of Professional Studies, Northeastern University

Trends in Trusted Data
The explosive growth of data and the value it creates calls on data professionals to level up their programs to build, demonstrate, and maintain trust. The days of fine print, pre-ticked boxes, and data hoarding are gone and strong collaboration from data, privacy, marketing and ethics teams is necessary to design trustworthy data-driven practices. Learn how to build trust in data practices.
Speaker:

, Lead Solutions Engineer, OneTrust

 

Reception in the Data Solutions Showcase

05:00 PM2022-05-172022-05-17

Tuesday, May 17: 5:00 p.m. - 6:00 p.m.

Wednesday, May 18

Keynote

Moderator:
Marydee Ojala, Editor-in-Chief, Online Searcher Magazine, USA
 

Continental Breakfast

08:00 AM2022-05-182022-05-18

Wednesday, May 18: 8:00 a.m. - 8:45 a.m.

 

Keynote: Data Quality Deniers & What We learn From Them

08:45 AM2022-05-182022-05-18

Wednesday, May 18: 8:45 a.m. - 9:30 a.m.

One of the biggest organizational obstacles to data quality management is basic pessimism about the possibility of managing the quality of data. This is due to lack of clarity—the goals and processes for data quality management have not been defined or have not been understood—and disbelief that the quality of data could be subject to control. Sebastian-Coleman describes the forms of data quality denial and what any organization facing data quality issues can learn from them. She addresses how to get beyond denial to a place where organizations improve the quality of their data to more effectively leverage its value.

Speaker:

, Data Quality Director, Prudential Financial

 

Using A Semantic Layer To Drive AI & BI Impact At Scale

09:30 AM2022-05-182022-05-18

Wednesday, May 18: 9:30 a.m. - 9:45 a.m.

Using a semantic layer makes data accessible and accelerates the business impact of AI and BI at your organization. Youssef offers practical advice, and real-life enterprise examples on how to modernize your data and analytics stack and achieve quantifiable results with an order of magnitude better query performance, increased productivity, lower query compute costs, and improved Speed to Insights.

Speaker:

, Sales Engineer, AtScale

 

Innovating With Graph Database Technology

09:45 AM2022-05-182022-05-18

Wednesday, May 18: 9:45 a.m. - 10:00 a.m.

From powering NASA’s mission to Mars to driving business innovation for Fortune 500 companies, graph database tech[1]nology is delivering value to organizations across the globe. Hear how companies are using graph database platforms to outpace their competitors and power business-critical appli[1]cations, along with real-world use cases that include fraud detection, analytics, AI/ML, and supply chain management.

Speaker:

, Regional VP, Neo4j

 

Coffee Break in the Data Solutions Showcase

10:00 AM2022-05-182022-05-18

Wednesday, May 18: 10:00 a.m. - 10:45 a.m.

 

Wednesday, May 18

Track A: What’s Next in Data & Analytics Architecture

Moderator:
Christine (Chrissy) Geluk, Principal & Founder, Librarian At Your Service LLC

What’s Next in Data and Analytics Architecture drills down on shifting trends and emerging approaches that are helping companies achieve more flexible, modular, and distributed data infrastructures to support modernization and innovation. Attend this track to gain a deeper understanding of the new technologies and strategies driving greater speed and scale, and improved governance and security, at organizations hungry for fast, actionable insights.

Designed for chief information officers, chief data officers, enterprise architects, data architects, data engineers, data scientists, data management and analytics professionals.

 

A201. Taking Your Data & Analytics to the Cloud

10:45 AM2022-05-182022-05-18

Wednesday, May 18: 10:45 a.m. - 11:30 a.m.

A recent survey of IT leaders found that the major­ity view hybrid or multi-cloud data warehousing as one of the most important data warehousing-re­lated trends. Today, the question is not whether to move to the cloud, but rather, which cloud platform is best for each organization’s needs.

Learn, Unlearn, Relearn: Embracing the Future of Cloud Analytics
Companies now collect more data than ever before, but challenges remain for accessing and analyzing them. Armlin suggests learning about the forces changing enterprise data architectures, unlearning the shortcomings of current architectures, and relearning a powerful new approach to data analytics in the cloud.
Speaker:

, VP Solution Architect & Customer Success, ChaosSearch

Journey to Cloud Analytics: How Companies’ Analytics Challenges Can be Solved by Moving to the Cloud
When moving analytics and BI workloads to the cloud, companies must develop, design, and deliver their data analytics differently. Faced with so many options to choose from, however, companies are unsure exactly what their analytics journey to the cloud will entail. Hoblitzell explains the key benefits and advantages of moving to the cloud, new capabilities for analytics, and what to look for when considering a partner to assist with an analytics cloud migration.
Speaker:

, VP, Data Management, Datavail

 

A202. Tapping Into the Internet of Things

11:45 AM2022-05-182022-05-18

Wednesday, May 18: 11:45 a.m. - 12:30 p.m.

The Internet of Things (IoT), once an emerging space, is quickly transforming industries by enabling machinery and products with network connectivity. From optimizing industrial machinery and manufacturing processes to powering connected cars and healthcare equipment, IoT-centered innovation is bringing about a future powered by data.

Solving the IoT Data Management Puzzle With Gateways to the Cloud

As sensor technology becomes more affordable, companies of all sizes will have the ability to embrace IoT strategies to build innovative products and services and establish new revenue streams. Yet, as with any promising technology, challenges remain. To reap the full value of IoT devices, companies need to migrate petabytes of IoT data quickly and securely to the cloud. As organizations across industries explore IoT offerings to strengthen consumer experiences and build new revenue streams, they must first understand its unique data management and orchestration challenges. This presentation explores best practices for activating data from the edge to cloud environments and activating this data to build new revenue streams.

Speaker:

, CTO, WANdisco

 

A203. Stream Processing With Apache Kafka

02:00 PM2022-05-182022-05-18

Wednesday, May 18: 2:00 p.m. - 2:45 p.m.

It is the goal of many organizations to continuously leverage intelligence from fast-moving event streams to help automate business decisions. Learn the best practices for utilizing streaming data to support modern applications.

Automating Business Decisions With Continuous Intelligence Using Event Streams

To deliver continuously useful insights, apps always need to have an answer from the latest data. Algorithms have to analyze, train, and predict continuously, and each new event must be analyzed in real time as soon as it arrives. As a result, insights and predictions are necessarily “given data thus far,” and the outputs therefore also form a real-time stream. This session provides a working example using streaming events from Apache Kafka and show attendees how to build applications that analyze, learn, and predict on-the-fly. This approach enables applications to self-assemble from streaming data, and applications are millions of times faster than “microservice plus database” architectures. It also gives developers new ways to ensure timely responses and to manage the effects of partitioning on event-driven applications.

Speaker:

, Head of Product Marketing, Swim

 

A204. How to Use In-App Ratings to Personalize and Improve Your User Experience

03:00 PM2022-05-182022-05-18

Wednesday, May 18: 3:00 p.m. - 3:45 p.m.

Product teams must realize the need for instrumenting the product to collect accurate data. Most teams tend to neglect the instrumentation process and later scramble to gather insights from data. If product teams don’t include or prioritize instrumentation as part of their road map, they run a risk of not capturing user behavior.

How to Use In-App Ratings to Personalize and Improve Your User Experience

App Store ratings aren't very helpful when it comes to better understanding customers. In-app ratings and feedback, however, can provide valuable insights into the behaviors and preferences of your users. In this session, you'll learn how to use in-app feedback to personalize and improve your user experience, including through the development of Artificial Intelligence models.

Speaker:

, Principal Engineer, Verizon

 

Wednesday, May 18

Track B: The Future of Data Warehouses, Data Lakes, & Data Hubs

Moderator:
Wayne Eckerson, President, Eckerson Group

The Future of Data Lakes, Data Warehouse and Data Hubs explores the growing array of repositories for storing, organizing, and sharing enterprise data, the impact of hybrid, multi-cloud, and distributed cloud computing on modernization strategies, and the development of new concepts such as data lake houses and data meshes. Attend this track to navigate the latest technologies and techniques underpinning the increasingly hybrid, real-time world of data.

Designed for chief information officers, chief data officers, enterprise architects, data architects, data engineers, data scientists, data management and analytics professionals.

 

B201. Future-Proofing Data Warehousing

10:45 AM2022-05-182022-05-18

Wednesday, May 18: 10:45 a.m. - 11:30 a.m.

The coming decade is going to require a modern data warehouse to meet demanding new requirements for machine learning, data variety, and real-time analytics—while still satisfying the more traditional need for analysis of structured data at scale.  

How to Select Your Cloud Data Warehouse Platform Strategically

Vendor claims to the contrary, data warehouse scale, performance, and operational issues are trickier than ever in the cloud. Choosing the wrong cloud database can result in millions of dollars of excess cost, unacceptable performance problems, or a drastically compromised database design. Winter provides a concise, strategic view of the cloud data warehouse landscape, highlighting how cloud database engines differ and how to choose one that will work for you. This will help avoid platform mistakes that can get you into deep trouble in the coming years.

Speaker:

, CEO & Principal Consultant, Wintercorp LLC and Faculty Member, TDWI (tdwi.org)

Making the Case for Legacy Data in Modern Data Analytics Platforms

Modern data analytics platforms that fuel enterprise-wide data hubs are critical for decision making and information sharing. The problem? 

Integrating legacy data stores into these hubs is just plain hard, and there is no magic bullet. However, the best data hubs include all enterprise data. This session explores best practices for integrating legacy data sources, such as mainframe and IBM, into modern data analytics platforms such as Cloudera, Databricks, and Snowflake.
Speaker:

, Senior Director of Product Management, Precisely

 

B202. Modern Data Lake Essentials

11:45 AM2022-05-182022-05-18

Wednesday, May 18: 11:45 a.m. - 12:30 p.m.

As data storage and analytics in the cloud continue to grow, organizations are evaluating the essentials for success, such as scalability, efficiency, affordability, and security.

Building the Open Data Lakehouse
Data consumers need data for BI and analytics to make business decisions. But for most organizations, their current data infrastructure isn’t keeping up with demand. Developing analytics and getting them into production takes weeks to months. Plus, data tied to proprietary formats makes it difficult to support different types of analytics, such as BI and data science. Data teams struggle with brittle data pipelines, stale data, slow turnaround, and increasing costs. A data lakehouse built on an open data architecture enables data users to access data in their data lake directly via SQL queries, simplifies complexity, and makes life easier for data teams. Learn why more organizations are moving their analytics and BI to an open data lakehouse and how you can build a successful lakehouse strategy.
Speaker:

, VP Product Management, Dremio

 

B203. Drilling Down on Data Lake Architecture

02:00 PM2022-05-182022-05-18

Wednesday, May 18: 2:00 p.m. - 2:45 p.m.

New ways to store data and leverage it in different ways are being utilized by data-driven organizations hungry for flexibility and scale.

Finding the Hidden Value in Data Lakes
Long associated with Hadoop, in a cloud world the data lake is often ignored in favor of its more fashionable cousins—mesh, fabric, lakehouse, and warehouse. But ignore the data lake at your peril, as it has an important role to play in any modern analytics strategy. Jablonski focuses on the evolving role of the data lake with a particular emphasis on: Why a data lake is a critical component of any cloud analytics project; the role of the data lake in the battle over ETL vs ELT; the importance of metadata in data platform design; and how a data lake helps deliver business value, not just technical success.
Speaker:

, VP, Analytics, Pythian

 

B204. Improving Data Quality in Data Lakes

03:00 PM2022-05-182022-05-18

Wednesday, May 18: 3:00 p.m. - 3:45 p.m.

For data to be useful, it must be trusted. It is important to standardize data, track its lineage, ensure that it is high quality, and verify that it is appropriate for the organizational roles or applications that leverage it.

Mapping Data Quality Concerns to Data Lake Zones

A common pattern in data lake and lakehouse design is structuring data into zones, with bronze, silver, and gold being typical labels. Each zone is suitable for different workloads and different consumers. For instance, machine learning algorithms typically process against bronze or silver, while analytic dashboards often query gold. This prompts the question: Which layer is best suited for applying data quality rules and actions? The answer: All of them. This presentation delves deeper into this answer, describing the purposes of the different zones and mapping the categories of data quality relevant for each by assessing its qualitative requirements. Bryson also covers data enrichment—the practice of making observed anomalies available as inputs to downstream data pipelines.

Speaker:

, Chief Customer Officer, Qualytics

 

Wednesday, May 18

Track C: Database & DevOps Boot Camp

Moderator:
Joe McKendrick, Principal Researcher, Unisphere Research, A Division of Information Today, Inc.

Now, more than ever, your company needs agility to navigate today’s rapidly changing business world. Therefore, it’s no surprise that DataOps continues to gain a foothold at enterprises seeking quick, actionable insights. The ability to make better decisions, faster, is a goal shared by many enterprises. At the same time, implementing an effective DataOps program requires significant technology, process, and cultural changes. At DataOps Boot Camp, you’ll hear about key supporting technologies, strategies, real-world success stories, and how to get started on your DataOps journey.

Designed for data scientists, data architects, and data engineers, as well as technology decision-makers and administrators. Both DataOps veterans and novices are welcome.

 

C201. Bringing DevOps to the Database World

10:45 AM2022-05-182022-05-18

Wednesday, May 18: 10:45 a.m. - 11:30 a.m.

DevOps and databases share many common characteristics. They shouldn’t be positioned as being at odds with each other.

What Is DevOps & Why Should DBAs Care?

You may have heard the term “DevOps” a lot lately, but is this just one of those buzzwords that gets thrown around and means something different depending on who’s talking? While traditional software methodologies pit developers and operations folks against each other, DevOps requires that they work together for a common goal. And, ultimately, shouldn’t the software project’s success be everyone’s goal? Come and learn how DevOps is changing the DBAs world for the better.

Speaker:

, Editor & DevOps Advocate, Redgate

How Data Professionals Can Participate in DevOps

Those of us who administer production databases have had to endure significant change relative to how the databases and applications we support are managed. This session introduces DevOps concepts and explain what their impact is on how database administrators and developers manage their infrastructures.

Speaker:

, Senior Solutions Architect, Quest Software

 

C202. The Evolution of Database Management

11:45 AM2022-05-182022-05-18

Wednesday, May 18: 11:45 a.m. - 12:30 p.m.

The care and feeding (aka management) of databases takes on new meaning in the Internet of Things era.

Rethinking the Database in the IoT Era
The internet has evolved from a human-centric, client-server-based architecture to one where humans and assets (or things) are equal stakeholders. Do our databases, middleware, and client applications still stand up? Gilmore outlines the unique challenges of data operations and analytics in the IoT environment, examines how human and machine interactions drive architecture and deployment, and identifies where we could work to improve our data strategies to fully leverage the IoT opportunity. 
Speaker:

, Director, IoT and Emerging Technology, InfluxData

Scaling Both Writes and Reads with Distributed SQL

Popular wisdom is that cache is king and you can easily scale by fronting your database with caching services like Redis. Moreover, you can scale out your relational database with read replicas. Finally, if that doesn't do it, you can choose a NoSQL database. However, what do you do when you have a lot of writes and a lot of reads, data integrity is critical, and downtime is a nonstarter? A new technology called distributed SQL borrows the best from both relational and NoSQL databases giving you both read and write scale while also ensuring the data is correct. As critical systems, financial systems, and the entire back office moves to the cloud, distributed SQL is key to ensuring data is consistent, available and scalable.

Speaker:

, Senior Director of Product Marketing, MariaDB Corporation

 

C203. Understanding Software Licensing Today

02:00 PM2022-05-182022-05-18

Wednesday, May 18: 2:00 p.m. - 2:45 a.m.

Licensing has always been tricky but the rise of trolling has created many new things to guard against.

Beware Software License Trolls, the New Danger

Any organization that has gone through a vendor software licensing audit knows firsthand how expensive and draining a process can be for an organization. No one disputes that companies like Oracle, Microsoft, or IBM have a right to be fairly compensated for the use of their software. The same safeguards these organizations put in place to protect their intellectual property can easily be distorted by a software troll against an unsuspecting company to extort millions of dollars. Learn about software license trolls and simple steps to take to ensure your organization is not their next victim.

Speakers:

, Chief Operating Officer, LicenseFortress, Inc

, Sr Product Line Marketing Manager & Chief of Staff for BCA, CIBG, VMware

 

C204. [This Session Has Been Cancelled] Data Exhaust or Exhausting Data?

03:00 PM2022-05-182022-05-18

Wednesday, May 18: 3:00 p.m. - 3:45 p.m.

[This session has been canceled due to unforeseen circumstances. We apologize for any inconvenience.]

The notion of data exhaust, all that peripheral data floating around in your organization, can have value to your business operations. It could help with predictive analytics, for example, or customer analysis. But as big data gets even bigger, are we exhausted by all the data at our fingertips? At what point does technology step in to help and which technologies are best suited to deal with data exhaustion? That’s what this panel considers.

 

Wednesday, May 18

Track AI: AI & Machine Learning Summit

Moderator:
Heather Hedden, Data & Knowledge Engineer, Semantic Web Company, USA,

The adoption of AI and machine learning (ML) technologies has become mainstream at businesses hungry for greater automation and intelligence with innovative use cases spreading across industries. A strong data management foundation is essential to effectively scaling AI and ML programs to deliver repeatable business value. To equip you with the knowledge to succeed, we are bringing together the leading industry experts for a 2-day immersion into real-world deployments, strategies for overcoming common business and technical barriers and key technologies every organization should know about.

Designed for chief information officers, chief data officers, data scientists, data engineers, enterprise architects, data analytics directors/managers, application developers and tech-savvy business leaders.

 

AI201. Unlocking Your Data With AI & ML

10:45 AM2022-05-182022-05-18

Wednesday, May 18: 10:45 a.m. - 11:30 a.m.

Data within the enterprise is useless if it can’t be found and used. AI and ML provide some pathways to data discovery that give companies competitive advantage.

Accelerating Your DevOps Journey With ML

Machine learning is both a buzzword and the Holy Grail, depending on how you use it. Enterprise cloud companies use machine learning to accelerate or supercharge their data journey—it helps them work at a faster pace, with more efficiency and greater accuracy. Once AI is fully in use, teams need to be able to answer this question: How do we know if this is working correctly? In order to do this, teams must extend their existing observability approaches to cover their AI and ML capabilities. Today, there’s a big gap there, and that creates risk as organizations can’t manage those assets properly. This session takes a deep dive into how companies utilize machine learning to take every competitive advantage to advance their ability to use all the data at their disposal.

Speaker:

, Senior Director, Product Management, Sumo Logic

 

AI202. Building a Streaming ML Platform

11:45 AM2022-05-182022-05-18

Wednesday, May 18: 11:45 a.m. - 12:30 p.m.

A single view of the customer, powered by AI and ML, can help identify fraud, personalize recommendations, and contribute to outstanding customer care encounters.

Customer 360 in a Box

With the advent of omnichannel, leveraging customer data has become paramount. In a behemoth such as Walmart, each customer’s identity exists as a silo rather than a single customer from the company perspective. Handling customer data for privacy, regulations, and deprecation becomes challenging with every new ID introduced in the system. A streaming ML platform that seamlessly combines data belonging to the same customer on a single box and runs ML models, which use this data as features, leads to a single view of a customer. Brar discusses the platform (built on Kafka ecosystem) and its important aspects.

Speaker:

, Staff Engineer, Walmart Global Tech

 

AI203. Rethinking Architectures for AI

02:00 PM2022-05-182022-05-18

Wednesday, May 18: 2:00 p.m. - 2:45 p.m.

As the world becomes increasingly data-driven, AI/ML algorithms are being incorporated in most business applications.

The Era of Distributed AI Architectures

Historically, data in AI architectures was moved to a central location to perform both model training and inference. This centralized approach is becoming untenable due to cost, performance, and privacy reasons. In this talk, Kaladhar shares his thoughts on next-generation distributed AI architectures and presents the concepts of “AI Marketplaces” and “Federated AI” to demonstrate how these concepts are an integral part of distributed AI architectures.

Speaker:

, Senior Fellow, Technology & Architecture, Office of the CTO, Equinix

 

AI204. Operationalizing AI: Challenges & Opportunities

03:00 PM2022-05-182022-05-18

Wednesday, May 18: 3:00 p.m. - 3:45 p.m.

Putting AI to work to improve healthcare requires having technology and infrastructure coupled with the right people.

Insights for Unlocking the Potential of AI in Healthcare

Healthcare innovators are innovators are prioritizing AI and operationalizing it for better performance, better outcomes, and better patient experience. But getting into predictive and prescriptive analytics takes many of them out of their comfort zones. Yet with every opportunity for improvement, there is a risk that organizations won’t have what it takes to successfully develop, implement, or operationalize AI. Having the technology and infrastructure for AI is not enough. Having the right people—with the technical capability and healthcare expertise—is enormously important. In this talk, Mehrotra and Fernando provide insight into strategies and plans to attract and retain the talent needed to unlock the potential of AI.

Speakers:

, SVP, Analytics, Optum Advisory Services

, SVP, Optum

Wednesday, May 18

Keynotes

Moderator:
Marydee Ojala, Editor-in-Chief, Online Searcher Magazine, USA
 

Closing Keynote: Data Architecture as a Service: The Culmination of the Self-Service Revolution

04:00 PM2022-05-182022-05-18

Wednesday, May 18: 4:00 p.m. - 5:00 p.m.

Data architecture-as-a-service is a verbal twist on cloud processing environments, such as software-as-a-service or platform-as-a-service. This moniker conveys that it’s possible to abstract architecture and build it into easy-to-use, customer-facing tools. When we abstract data architecture, we solve the most enduring data pain point in the data world: the proliferation of data silos and pipelines that wreak havoc on data consistency and trustworthiness.

Speaker:

, President, Eckerson Group

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