Data fabric and data mesh are not mutually exclusive. Join us in this two-speaker debate session that aims to put an end to a five-year long debate comparing fabric and mesh. D&A leaders can deploy them independently, or best-case together. You will find out how you can deploy the fabric design to unify data management and mesh operating model to distribute data management.
talk-data.com
Event
gartner-data-analytics-india-2025
Activities tracked
8
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Sessions & talks
Showing 1–8 of 8 · Newest first
Acceldata: Rethinking Enterprise Data Management: Autonomy and Intelligence for the AI Era
In a fragmented data landscape, reactive processes trap enterprise teams in firefighting mode, hindering innovation and scalability.Acceldata’s Agentic Data Management introduces a new paradigm, embedding proactive, AI-driven autonomy and cross-domain intelligence into data operations. By eliminating bottlenecks and reducing manual burden, it accelerates trustworthy insights and scalable governance. Join Acceldata to discover how forward-thinking enterprises are modernizing their data strategies to power innovation—and why autonomous operations are essential for thriving in an AI-first world.
Data Fabric: Building and Managing Your Foundational and Long-Term Data Management Architecture
Urgent Investments in data, analytics and AI use cases has put the spotlight once more on strong data management foundations. Is our Data even Ready for upcoming AI, analytics and data sharing initiatives is now top of mindshare for heads of data, CDAOs and their counterparts. Data Fabrics have emerged as a long term, foundational data management architecture that you should now pursue for sustained D&A success. This session will:
1. Help understand what data Fabrics are and what they mean for your data strategy and architecture
2. Help decide how to build and where to buy
3. Navigate the vendor landscape to assist in tech procurement decisions to aid your fabric journey
Future of Data Management Using GenAI
Productivity and operational efficiency are one of the key measures of business performance and economics. GenAI has promising capabilities of improving productivity and operational efficiency of data management function, and data governance. Organizations should explore and assess those capabilities to align it with strategic goals to improve the productivity and operational efficiency.
Oracle: From Data to Decisions - Powering Business Outcomes with Oracle Data Intelligence
In today’s data-driven world, organizations are challenged to extract meaningful insights from complex, distributed information. A modern data intelligence platform brings together data management, AI/ML, and analytics to turn raw data into strategic advantage. This session explores how unified data architectures, augmented analytics, and intelligent applications are enabling smarter decisions and better business outcomes across industries. Real-world use cases—from demand forecasting to regulatory compliance—highlight the transformative impact of data intelligence. Powered by Oracle, this approach helps enterprises stay agile, informed, and competitive.
Simplify the Complex Data Management Infrastructure with Data Ecosystems
Data ecosystems, built on data fabric design and infused with AI, promise an integrated, cost effective, and operationally simple approach to varied data management challenges. However, they don't yet always deliver on that promise. This research explores the maturity of various ecosystem components and provides a guide for D&A leaders and others looking to invest in data foundations for competitive differentiation.
DataOps: Delivering Operational Excellence in Data Management
D&A leaders must develop DataOps as an essential practice to redefine their data management operations. This involves establishing business value before pursuing significant data engineering initiatives, and preventing duplicated efforts undertaken by different teams in managing the common metadata, security and observability of information assets within the data platforms.
Unlocking the Future: How Python, Spark and Open Table Formats are Revolutionizing D&A Architectures
It's now easier than ever for less technical users to access, manage and analyze data without needing help from IT. But, self-service data management isn't always straightforward, and there are plenty of pitfalls, like data quality issues, skills gaps and governance concerns. This session will cover practical ways to make self-service data management work.