2How can you design and deliver a modern data centric architecture (data lakes, data warehouses, data hubs, cloud) that enables digital transformation?
The Future of Data Management
Data Management Solutions for Analytics — Why Hadoop Won’t Replace Your Data Warehouse Anytime Soon
How to Avoid Data Lake Failures
Shifting Data Integration from Reactive to Proactive “in the Business Moment”
From Self-Service to Enterprise Data Preparation: Learn to Implement and Operationalize Data Preparation for Data and Analytics Success
Adopt a Data Hub Strategy for Controlled and Streamlined Data Sharing
Data Hubs, Lakes and Warehouses: Choosing the Core of Your Data and Analytics Platform
Magic Quadrant for Data Management Solutions for Analytics
Ask the Expert: Choosing On-Premises vs. Cloud for Data Infrastructure
Roundtable: Getting More From the Data Lake
Learn about competing and complementary options in data management, and how they are used to supercharge your existing business or to pursue net-new products and business models towards analytics, data science and operational use cases
Understand how data warehouse architecture has to evolve to a more modern logical data warehouse architecture in order to meet these demands in both distributed and centralized solutions
3How can you harness the latest trends such as AI, IoT, data science, machine learning in data and analytics to drive innovation?
AI in Data Management Is Real: Navigating the Rise of Augmented Data Management
Top Technology Trends in Data and Analytics That Will Change Your Business
How the Internet of Things Will Disrupt Your Data and Analytics Capabilities
How Augmented Analytics Is Transforming Data Science and Machine Learning
Making Machine Learning Explainable: Unravelling the Mysteries of the Black Boxes
Blockchain for Data Management: How the World’s Worst Database Will Work for You
Advanced Analytics: Tales From the Cutting Edge Alexander Linden
Innovative Analytics in Action: Emerging Trends You Need to Know
Magic Quadrant for Data Science and Machine Learning Platforms
Ask the Expert: Stream Analytics Trends, Tools and Best Practices
Ask the Expert: Key Trends in Data Management and Integration
Learn about the leading edge technologies, architectures and best practices in data and analytics and how they will impact your digital business requirements now and in the future
Get insight into the most important and impactful current and upcoming business, technology and market trends needed for your organizations key D&A initiatives
Understand how the IoT creates new data and analytics challenges and what must data and analytics leaders do to drive adaptation for the IoT as well as which new capabilities will be critical to success
Learn what challenges are creating a need for AI in data management and how will AI augmentation will enhance data management infrastructure
6How can you build data-driven culture, improve organization’s data literacy, build effective programs to drive your data and analytics initiatives; and accelerate adoptions?
The Data-Driven Organization: How to Create and Lead High- Performing Data and Analytics Teams
Your Data Culture is Changing — Do You Need DataOps?
Use Continuous Intelligence to Transform the Business
CDO Circle: Leadership Exchange — How CDOs Can Drive a Data-Driven Culture Using Data Literacy
Workshop: Overcoming Change Resistance: The First Step to Becoming a Data-Driven Organization
In the diverse and often chaotic world of data and analytics — the business often struggles to understand and then interpret their investments in and outcomes from data and analytics. Learn from experts on how Data Literacy is becoming a must have discipline to help the business propagate, evangelize and understand the value of data and analytics and connect it to business outcomes.
Empower everyone and everything in the organization to leverage data and analytics to optimize every decision, every process and every action
Learn what the new discipline of DataOps means and how you can implement some early practices in your organization
7How can you make data and analytics pervasive in your organization (for example, embedded in applications, across business domains and functions), and utilize the key trends of augmented analytics or selfservice to your advantage?
How to Choose the Right Line of Business Analytic Application
The Future of Data and Analytics: How Augmented Analytics Will Transform Your Organization
From BI to AI: Build the Business-Driven Data and Analytics Architecture
Upgrade from Self-Service to Enterprise Data Preparation for Analytics and Data Science Success
Magic Quadrant for Analytics and Business Intelligence Platforms
Build a portfolio of innovative and relevant business and industry-specific analytic applications
Learn where to find analytic applications and what are the most important things to consider in evaluating different vendor options in analytics, data management and data science/machine learning
Discover the step-by-step methodology to design a businessoutcomes-driven analytics evolution roadmap with a strong commitment to users and a shift from technology to business impact
12What are the critical factors in effectively governing data, analytics and AI?
Early Lessons and Next Practices of AI Governance
The Foundation and Future of Data and Analytics Governance
Metadata Management Is a Must Have Discipline
The Foundation of Master Data Management
How to Evolve Data Quality Programs for Best Business Impacts
Ask the Expert: DataOps — Organizing for Trusted Data-Driven
Lead by building a foundation of trust, accountability, governance, security and privacy
Learn how to establish solid foundations needed for successful data and analytics governance today, and the future direction of governance as it evolves to address new business and technology challenges
Get clarity on how can metadata management deliver value and how to set up a metadata management practice