Three of us friends are working on "Data Engineer in a box" or "Cursor for Data": https://getnile.ai
Our thesis is that a lot of Data Engineering practiced today is non-differentiated across companies and they'd rather spend that time on differentiated tasks. What if we can abstract away a lot of the tedious parts of DE work and let companies focus on just the data they want to store, and the questions they have on their data?
So today, we have an MVP that manages the compute, storage, lineage, versioning and pipeline building for datasets. Would LOVE to get feedback on this or your early thoughts!
Our thesis is that a lot of Data Engineering practiced today is non-differentiated across companies and they'd rather spend that time on differentiated tasks. What if we can abstract away a lot of the tedious parts of DE work and let companies focus on just the data they want to store, and the questions they have on their data?
So today, we have an MVP that manages the compute, storage, lineage, versioning and pipeline building for datasets. Would LOVE to get feedback on this or your early thoughts!