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.

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.

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.

AI-powered Data Engineering Agents usher in a new era of data agility. Engage with Google Cloud and your peers to explore the implementation of autonomous data agents and their impact on enterprise agility. From automating data pipelines to ingestion to transformation, discover how to leverage autonomous data agents to build self-managing data ecosystems and accelerate the time from raw data to impactful decisions. This is where data's potential truly meets AI power.

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 integration is evergreen, serving as a foundation element for any resilient data management strategy.
This session gives guidance on:
1. Data engineering top practices: What are the best practices to improve data integration?
2. Technology trends: What are the trends guiding the data integration technology?
3. Prioritization: Which of these top practices would prove to be the most impactful to your organization, given your current level of maturity?