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1. Some low-code data exploration options include using the ydata library, in-cell data profile, Databricks Assistant, and AutoML.
2. Databricks Assistant is useful for data exploration when you have a good idea of the analyses you want to build and you want code assistance. Databricks Assistant is a great way to speed up the coding process or augment your SQL knowledge. On the other hand, AutoML is very useful for automatically creating a profile notebook that broadly covers your dataset.
3. We would use Delta Live Tables to set expectations. Expectations are a way to flexibly handle data abnormalities and give the options to report bad data, drop that data, or fail the pipeline entirely.
4. Regular databases, or relational databases, are designed for data in tabular form, typically organized in rows or columns. A vector database is designed to store vector data, such as embeddings and high-dimensional...