Modern product teams are increasingly reliant on large volumes of data generated by feature releases, customer interactions, and event streams, which complicates the validation of results and quick resolution of discrepancies. Product Analytics addresses this challenge by offering transparency into the SQL queries behind charts and providing data tables for trends and funnels. These features allow teams to validate definitions, debug faster, and explore underlying numbers, enhancing their ability to analyze and share insights. By viewing and manipulating SQL queries, teams can understand how metrics are calculated, make necessary adjustments, and ensure alignment with stakeholders. Data tables complement charts by offering detailed views of trends and funnels, facilitating in-depth analysis and comparison of segments, which can be crucial for identifying issues such as conversion drop-offs. This capability empowers teams to move from high-level observations to data-driven conclusions, fostering a collaborative and evidence-based decision-making process.