Data Integration Leaders Summit: Session Recordings
Hear from data integration leaders and industry experts on how they turn integration into an asset across Operational, Analytics, and GenAI use cases.
Elevating Data Integration to Drive Innovation
This series is designed for leaders looking to modernize their organization’s data integration capabilities across analytics, operations and artificial intelligence use cases;
Leveraging integrated data to drive insights and inform business decisions.
Enhancing operational efficiency and app functionality with unified data.
Feeding data into vector databases to deploy generative AI use cases and train LLMs.
Enabling robust predictive models and analysis through comprehensive data aggregation.
Streamlining the secure exchange of data across systems and stakeholders.
Facilitating the preparation and management of data from multiple sources for analysis.
Summit Speakers
Summit Agenda
Join Saket and Cara to learn how data integration systems will evolve in the years ahead and the essential need for organizational evolution in the data-driven business landscape. Explore the transformation of business strategies and Chief Data Officer (CDO) roles, recognizing their pivotal role in driving success. Learn from real-life examples showcasing the transformative impact of data products.
In this session, we tackle the data engineering hurdles specific to financial services, focusing on reducing time to value for heterogeneous data and catering to diverse consumption patterns like operations, analytics, and AI.
The world of data can be chaotic, with spreadsheets overflowing and reports conflicting. In this session, Sangeeta will cover the common problems in data strategy and how to avoid them in the AI world, through the combination of data strategy and analytics tactics. This session will also discuss how to empower users to understand the “why” behind the numbers.
Becoming data-driven is about measurable outcomes and starts with generating new value streams from your (and others) data assets. Unfortunately however, most organizations have no defined process or function for monetizing their data. Join this session to learn insights from the best-selling book, “Infonomics”, and about the design, development and support of data products and services.
Learn how to transform data from ‘dumb’ to smart through analytical strategies, ensuring accuracy amidst uncertainty, and leveraging statistical findings for practical business impact.
Join us for a Q&A session with Apporv Saxena, Managing Director at SilverLake. With extensive experience in leading AI-driven transformation initiatives across a diverse portfolio, Apporv brings invaluable insights into harnessing the power of AI. This session will delve into practical strategies, challenges faced, and lessons learned from driving AI-driven transformation across various sectors.
In today’s world of digital innovation fueled by AI, harnessing the power of data transformation/integration has become more important than ever. In this talk, we will share best practices and emerging trends in the AI world to maximize the power of data. From data collection and storage to analysis and interpretation, we illuminate best practices that drive actionable insights and innovation.
In the ever-evolving landscape of e-commerce, Poshmark stands out as a prime example of leveraging data and AI to accelerate their business. Join Mahesh as he shares how Poshmark strategically uses AI across all facets of the company to drive a data-driven framework for growth, innovation, operational efficiency, and customer empowerment.
As data proliferates, the strategic development and integration of data products can be a consideration for enterprises aiming to stay ahead of evolving market demands and technological advancements. Join Colin as he shares an Executive-Level look at data products, their advantages in different levels of data maturity, and real-world examples with considerations into starting or evolving your Data Product Strategy.
Dive into mastering data complexity with Kannan and Renju at our summit: ‘Data Engineering in the Era of Modernization.’ Explore topics like modernizing data platforms, principles like data mesh, and addressing challenges of multi-cloud data access, featuring insights from LiveRamp’s experience integrating with 650 advertisers.
In today’ data-driven world, as organizations look to drive innovation, they are often held back by the sheer complexity of data integration and engineering. From the rise of GenAI to the transformative power of cloud technologies, this session will explore the strategies and best practices for achieving success in the digital age. Join us as we delve into key topics in data integration and engineering across various industries, overcoming challenges in analytics and business intelligence, optimizing data movement, innovation with metadata, and scaling data transformation efforts.
Dive deep into the core use cases of data integration as it pertains to analytics, operations, and artificial intelligence. Learn how integrating data can drive operational excellence, enhance analytical capabilities, and fuel AI innovations.
Gain insights into how effective data integration strategies can transform your analytics and operations, enabling more informed decision-making and streamlined business processes.
Understand the pivotal role of data integration in AI and machine learning projects. Discover how seamless integration can enhance model accuracy, speed up deployment, and unlock new AI-driven opportunities.
Ideal for those overseeing strategic data initiatives and looking to address challenges such as overloaded data engineering teams, lack of standardization, and high tooling costs.
Perfect for operational leaders focused on producing data solutions, dealing with the demand for custom solutions, and navigating the challenges of building and updating connectors.
Ideal for leaders managing core data platforms, focusing on operational excellence through data integration in systems and applications.
Suited for leaders in data usage roles, especially those who depend on engineering teams for data preparation and require solutions for real-time prediction capabilities.