This webinar offers a guide for data engineering leaders to evaluate such tools. We recommend five product evaluation criteria: breadth of functionality, ease of use, governance, performance and scalability, and cost. Data engineering leaders and their teams can use these criteria to compare commercial and homegrown options to one another, ensuring they have the right tool to enable GenAI innovation.

Join Kevin Petrie, VP of Research at BARC, and Luke Roquet, COO and co-founder of Datavolo, to learn:

● What GenAI is and how it works

● Why and how companies are applying GenAI language models to their data

● Criteria for data engineering teams to evaluate data pipeline tools in this space

● GenAI risks and governance techniques to mitigate them

● Guiding principles for successful implementation