Databricks Databricks-Certified-Data-Analyst-Associate Exam With Confidence Using Practice Dumps

Delta Lake is a storage layer that enhances data lakes with features like ACID transactions, schema enforcement, and time travel. While it stores table data as Parquet files, Delta Lake also keeps a transaction log (stored in the _delta_log directory) that contains detailed table metadata.

This metadata includes:

Table schema

Partitioning information

Data file paths

Transactional operations like inserts, updates, and deletes

Commit history and version control

This metadata is critical for supporting Delta Lake’s advanced capabilities such as time travel and efficient query execution. Delta Lake doesnotstore data summary visualizations or owner account information directly alongside the data files.

Markdown-based text boxes are useful as labels on a dashboard. They allow the data analyst to add text to a dashboard using the %md magic command in a notebook cell and then select the dashboard icon in the cell actions menu. The text can be formatted using markdown syntax and can include headings, lists, links, images, and more. The text boxes can be resized and moved around on the dashboard using the float layout option. References: Dashboards in notebooks, How to add text to a dashboard in Databricks

Query History in Databricks SQL is intended for reviewing executed queries, understanding their execution plans, and identifying performance issues or errors for debugging purposes. It allows users to analyze query duration, resources used, and potential bottlenecks. However, Query History does not provide any capability to automate the execution of queries across multiple warehouses; automation must be handled through jobs or external orchestration tools, not through the Query History feature itself.