First look at the Gartner Data & Analytics Summit agenda

We’re currently curating the full agenda for Gartner Data & Analytics Summit 2022, 9 - 11 May, in London, UK. 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

  • Three Neuroscientific Ideas to Supercharge Your Diversity, Equity and Inclusion Programs
  • Data-Driven Foundations: Getting Started With Data Literacy and Data-Driven Business Transformation
  • Proven Solutions to Talent Recruitment and Retention Challenges: A Review of Best-Practice Case Studies
  • Driving a Data-Driven Transformation Program
  • Scenario Planning: How D&A Leaders Can Provide Insight Into the Future
  • The Foundation of Organization and Roles: From Control to Collaborate
  • Selecting a D&A Service Provider — How to Choose the Right One for Your Organization

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
  • How to Create Metrics That Matter
  • The Foundation of a Modern Data and Analytics Strategy
  • How to Drive the Business Value of Data and Analytics
  • The Future of Data and Analytics — Reengineering the Decision, 2025
  • Keeping SCORE, Understanding Your D&A Maturity
  • The Foundation of an Effective Data and Analytics Operating Model

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

  • Built for Speed: How to Bootstrap an MDM Initiative
  • Metadata Is the Key to Self-Learning, Augmented Data Governance
  • The Foundations of Master Data Management
  • How New Technologies Like AI and Graph Are Transforming MDM
  • Digital Ethics: Where Are You Now and What Will Be Next?
  • Trusted Data Sharing for Optimal Business Value: Top Best Practices to Get It Right
  • Technical Insights: Building a Comprehensive Governance Framework for Data and Analytics
  • The Foundation and Future of Data and Analytics Governance
  • Data and Analytics Everywhere Needs Connected Governance
  • 12 Quick Actions to Improve Your Data Quality

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

  • Decisions: Can Data and Analytics Make Them Better?
  • How to Use Influencers Within Communities to Increase Data and Analytics Adoption
  • Scaling Analytics for Everyone Through Automation
  • Build Resilience and Agility Into Decisions Using X Analytics
  • How to Govern Self-Service Analytics
  • Use Composable Data and Analytics to Build Modular Business-Oriented Analytics Experiences
  • Data Storytelling: A Better Way to Engage Decision Makers With Data

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

Recommended sessions

  • The Future of Data Science and Machine Learning: Critical Trends You Can’t Ignore
  • Embed Data Privacy Within Data Science Solutions Using Synthetic Data and Other Techniques
  • Leveraging Agile Best Practices to Build a CollaborativeData Science Practice
  • Maximize Value by Extending to Predictive and Prescriptive Analytics
  • Struggling With Establishing Trust in AI? Reduce Model Bias and Incorporate Explainable AI
  • Bake-Off: Data Science and Machine Learning

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

  • Use AI Maturity Model to Do The Right Things at the Right Time
  • Synthetic Data: Why, When and How to Use It
  • Develop Your MLOps Playbook to Accelerate Machine Learning Deployment
  • How to Find Winning AI Use Cases
  • Bring It All Together — NLT, Computer Vision and More to Create Emotional Virtual Beings!
  • AI Engineering — Moving the AI Needle to the Next Level

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

  • Avoid Data Lake Failures by Addressing Modern Lake Requirements
  • Deploying Data and Analytics Architecture in AWS, Azure and GCP Cloud Platforms
  • The Evolution of Data Management Beyond 2022
  • Maximize Business Outcomes by Adopting Modern Data Catalog With AI-Enabled Metadata Capabilities
  • Data Warehouse Automation: Applying Agile DevOps and DataOps Principles to Your Deployments
  • Data Lakes, Data Warehouses and Data Hubs Aren’t the Same: Know Their Capabilities and Purpose
  • Cloud Is the Future of Database Management
  • Utilize Self-Service Data Preparation to Augment Rising Data Engineering Challenges
  • How to Design a Data Fabric for Augmented Data Management and Integration
  • Database Migration to the Cloud or Elsewhere: The Good,the Bad and the Ugly
  • Leverage Data and Analytics Ecosystems for Adaptability, Speed and Lower Cost.

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

  • Relating Data Fabric Fundamentals to the Business Drivers
  • AI and Climate Change: The Challenge, the Complexity and the Criticality
  • Top Data and Analytics Predicts
  • Top Trends in Data and Analytics for 2022
  • Edge Computing and Internet of Things Solutions: What to Know and How to Prepare
  • Seven Future AI Scenarios
  • Raise Your AI Game With Graph Analytics and Machine Learning
  • Decision Making and Optimization Across Your Enterprise and Ecosystem
  • Streaming Data in Motion: Collision of Messaging, Stream Analytics and DBMS