Ehtisham Zaidi

This session covers practical steps, common mistakes to avoid, and key factors for launching data and maintaining a data catalog. Discover how to assess your organization’s metadata requirements, define clear goals, and apply best practices for a smooth implementation and ongoing success.

Data management platforms emerge through the convergence of several individual data management capabilities. D&A leaders keen on data platform modernization should join this breakout session to learn about the dynamics of this emerging market and the benefits of reducing architectural silos to meet data demands for both current and innovative use cases.

Data management platforms emerge through the convergence of several individual data management capabilities. D&A leaders keen on data platform modernization should join this breakout session to learn about the dynamics of this emerging market and the benefits of reducing architectural silos to meet data demands for both current and innovative use cases.

Data integration tools help organizations access, process, move and transform data. They support use cases like data engineering, modern data architecture, less-technical/business user support and operational data integration. In this session, we'll present the latest Magic Quadrant for Data Integration Tools, discussing vendors and technologies to help you choose the best tool for your needs.

Data and analytics leaders and their data engineering teams are tasked with evaluating and selecting data integration tools. However, there are many options, which can be confusing. This session will explain the various types of data integration tools and technologies available in the market and help you select the right data integration tool for your needs.

Data fabric is the future-proof data management architecture to support both current and upcoming use cases, including AI-ready data. When it comes to building the data fabric architecture, most D&A leaders are confused regarding building the fabric from the ground up, using individual tools, versus buying the entire technology stack. Come with your questions, go with clarity.

This multigroup session will focus on questions like: - How should organizations implement AI governance frameworks to manage risk, ethics and accountability? - How can organizations prepare and assess their data, infrastructure and workforce to ensure AI readiness. - What are the best practices for the above questions and what are the challenges and barriers to implementation of those practices?

Data integration tools help organizations access, process, move and transform data. They support use cases like data engineering, modern data architecture, and operational data integration. In this session, we'll present the latest Magic Quadrant for Data Integration Tools, discussing vendors technologies to help you choose the best tool for your needs. We will also present the latest Maqic Quadrant for Metadata Management Tools that will help you select the most optimal metadata tool for your use cases.

D&A leaders have a key strategic decision to make over the next few years. What does their strategic and long-term data management platform looks like and where to source it from? There are four options that this session will discuss: utilizing the all encompassing data and AI platform from their cloud service providers, extending their ISV solution providers to enable their data platform, engaging their enterprise SaaS application providers to support D&A use cases, or taking a blended approach.