The data world is experiencing a theme of consolidation, with the past decade seeing a significant boom in the market followed by a current trend of tool consolidation. This can be attributed to acquisitions and the increased number of acquisitions in the data technology market. The impact of AI on day-to-day data engineering work is also growing, with AI capable of spinning up SQL queries that used to take much more time to write, but also unlikely to disrupt strategic elements such as understanding context, business logic, and strategy. Painful platform migrations are a common issue, often resulting from executive decisions made primarily on projected cost savings, sunk cost fallacy, and leadership being too far removed from the day-to-day reality of engineering. The migration of tools like Pandas is also worth considering, especially with its single-threaded architecture and memory inefficiency showing their age.