First look at the Gartner Data & Analytics Summit agenda

We’re currently curating the full agenda for Gartner Data & Analytics Summit 2022, March 14 – 17, in Orlando, FL. We are covering the most pressing topics in data and analytics such as: artificial intelligence (AI), machine learning (ML), augmented analytics, data fabrics, governance, privacy, leadership, culture and so much more.   

Below is a sample of the sessions we’ve already selected for the 2022 agenda.

Preliminary agenda sessions

Data and analytics leaders are expanding their sphere of influence and impact on the business. This track investigates critical topics such as unleashing innovation, redefining culture and building and managing creative teams.

Recommended sessions

  • Data-Driven Foundations: Getting Started With Data Literacy and Data-Driven Business Transformation
  • Driving a Data-Driven Transformation Program
  • Proven Solutions to Talent Recruitment and Retention Challenges: A Review of Best Practice Case Studies
  • Scenario Planning: How D&A Leaders Can Provide Insight Into the Future
  • Three Neuroscientific Ideas to Supercharge Your Diversity, Equity and Inclusion Programs
  • Why Every Organization Should Have a Chief Data Officer  

Data and analytics functions have always been critical to organizations, but now they have taken center stage as vital to business strategy. This track explores how to prioritize data and analytics investments and develop a strategy to ensure success. 

Recommended sessions

  • Accelerating Your Transition to Data and Analytics Product Management
  • FinOps Will Transform Your Financial Governance Approach to Cloud Data and Analytics
  • How to Drive the Business Value of Data and Analytics
  • How to Leverage Customer Data Management Technologies for Better Customer Experiences
  • Keeping SCORE, Understanding Your D&A Maturity
  • The Foundation of a Modern Data and Analytics Strategy
  • The Foundation of an Effective Data and Analytics Operating Model
  • The Future of Data and Analytics — Reengineering the Decision, 2025

Diversity, privacy, sustainability and other societal concerns are now top of mind with consumers. This track provides guidance for putting trusted, agile data and analytics and AI governance practices in place.

Recommended sessions

  • Data and Analytics Everywhere Needs Connected Governance
  • Digital Ethics: Where Are You Now and What Will Be Next?
  • How New Technologies Like AI and Graph Are Transforming MDM
  • How Sovereign Data Strategies Will Impact You and Your Organization
  • Prepare to Use Privacy-Enhancing Computation, and Other Top Privacy Trends
  • The Foundation and Future of Data and Analytics Governance
  • The Foundation of Data and Analytics Is Cloud!
  • The Foundations of Master Data Management
  • The Journey to Data and Analytics Governance Platforms
  • Trusted Data Sharing for Optimal Business Value: Top Best Practices to Get It Right

Digital acceleration and agility require analytics to be infused into every role, business process, decision and action. This track addresses how to make analytics fundamental to all parts of the business in a trusted way. 

Recommended sessions

  • A Netflix for Analytics: How to Establish a Powerful Delivery Channel to Decision Makers
  • Build Resilience and Agility Into Decisions Using X Analytics
  • Data Storytelling: A Better Way to Engage Decision Makers With Data 
  • How to Govern Self-Service Analytics
  • How to Use Influencers Within Communities to Increase Data and Analytics Adoption
  • Rethink Self-Service: Establish Analytic Franchises to Drive Adoption, Break Bottlenecks and Maximize Value
  • Use Composable Data and Analytics to Build Modular Business-Oriented Analytics Experiences

Developing and operationalizing data science and ML can be daunting. This track is dedicated to exploring the strategies, tools, skills and talent needed for successful deployment. 

Recommended sessions

  • Embed Data Privacy Within Data Science Solutions Using Synthetic Data and Other Techniques
  • Leveraging Agile Best Practices to Build a Collaborative Data Science Practice
  • Maximize Value by Extending to Predictive and Prescriptive Analytics
  • The Future of Data Science and Machine Learning: Critical Trends You Can’t Ignore

To realize its great potential, AI must go beyond experimentation and prototyping. This track addresses value opportunities, operating models, roles and skills, technology trends and best practices to turn AI’s promise into a reality. 

Recommended sessions

  • AI and Customer Analytics: Now and Next
  • AI Engineering: Moving the AI Needle to the Next Level
  • Bring It All Together: NLT, Computer Vision and More to Create Emotional Virtual Beings!
  • Develop Your MLOps Playbook to Accelerate Machine Learning Deployment
  • How to Find Winning AI Use Cases
  • Responsible AI Means Responsible and Ethical Humans: Be One of Them
  • What Data and Analytics Leaders Need to Do About Decision Thinking

Digital acceleration requires that enterprises transition from being data-driven to being data-and-analytics-centric. This track explores how to architect disparate data and analytics capabilities across your various data and analytics vendors and solutions.

Recommended sessions

  • 12 Quick Actions to Improve Your Data Quality
  • Avoid Data Lake Failures by Addressing Modern Lake Requirements
  • Data Lakes, Data Warehouses and Data Hubs Aren’t the Same: Know Their Capabilities and Purpose
  • Data Warehouse Automation: Applying Agile DevOps and DataOps Principles to Your Deployments
  • Database Migration to the Cloud or Elsewhere: The Good, the Bad and the Ugly
  • Deploying Data and Analytics Architecture in AWS, Azure and GCP Cloud Platforms
  • Driving Analytics Success With Data Engineering
  • How Data and Analytics Leaders Can Leverage Integration Strategies to Thrive in Times of Uncertainty
  • Leverage Data and Analytics Ecosystems for Adaptability, Speed and Lower Cost
  • Maximize Business Outcome by Adopting Modern Data Catalog With AI-Enabled Metadata Capabilities
  • Streaming Data in Motion: Collision of Messaging, Stream Analytics and DBMS
  • Utilize Self-Service Data Preparation to Augment Rising Data Engineering Challenges

Harnessing innovative technologies to change business models and define new ways to interact with and serve customers, partners, suppliers and employees is a top priority. This track explores emerging trends reshaping business today.

Recommended sessions

  • Adaptive Systems: The Next Stage of AI Solutions
  • Daring Decisions Can Be Safer With Artificial Intelligence
  • Edge Computing and Internet of Things Solutions: What to Know and How to Prepare
  • Effectively Leveraging Data Marketplaces and Exchanges as a Data and Analytics Leader
  • Raise Your AI Game With Graph Analytics and Machine Learning
  • Seven Future AI Scenarios
  • Top Data and Analytics Predicts
  • Top Trends in Data and Analytics for 2022
  • XOps: Apply DevOps Practices to Transform Data, Analytics and AI Delivery