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Snowflake Cloud - Data engineering
Batch starting from 31st Aug.
Enrollments will close by 7pm ist tmrw

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Note - enrollments for Snowflake cloud batch starting tomorrow will close by 7 pm ist.. hurry up if you want to enroll..

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Correct answer is stage

Stage object can be cloned

𝐒𝐐𝐋 𝐐𝐮𝐞𝐫𝐲 𝐎𝐩𝐭𝐢𝐦𝐢𝐳𝐚𝐭𝐢𝐨𝐧 𝐏𝐫𝐨 𝐓𝐢𝐩𝐬! Are your SQL queries experiencing a slowdown? It's time to ramp up your database performance with these 20 expert tips! 💡
1: Preferably, use UNION ALL for faster query results unless removing duplicates is essential.
2: Avoid using OR in join conditions to prevent substantial impacts on query speed.
3: Use UNION instead of UNION ALL when eliminating duplicates from combined queries.
4: Minimize network latency by performing computations or filtering closer to the database using stored procedures.
5: Regularly update statistics and indexes on tables to ensure optimal query execution plans. 6: Simplify and improve code readability by restructuring subqueries for better efficiency. 7: Minimize using functions on the right-hand side of operators for smoother query execution.
8: Employ EXISTS rather than DISTINCT in one-to-many table joins to boost query performance.
9: Specify individual column names instead of using '*' in SELECT statements for improved accuracy and speed. 10: Optimize JOIN order by arranging joins based on the smallest result set first for faster processing.
11: Streamline queries by eliminating redundant mathematical operations, promoting a simpler and faster approach.
12: Leverage the IN predicate when working with indexed columns for enhanced query efficiency.
13: Break down complex queries into smaller, more manageable parts for improved execution time.
14: Implement query caching to store frequently executed queries for faster retrieval.
15: Profile query performance using tools like EXPLAIN or query execution plans to identify bottlenecks.
16: Avoid unnecessary nesting or chaining of views to reduce query complexity and improve performance.
17: Use the HAVING clause judiciously within SELECT statements to prevent potential query slowdowns.
18: Consider selective database denormalization to reduce JOINs and boost query speed for specific operations.
19: Reduce the use of DISTINCT conditions to only necessary instances for quicker query performance.
20: Regularly review and fine-tune your queries for enhanced efficiency and optimal performance.

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Answer is one... Star schema has one fact with N number of dimensions around it.. Snowflake schema you have fact table with dimensions around with dimensions connected to another dimensions

Snowflake playing nicely with other data lakes:
At this time Snowflake supports three external tables or external stages: AWS S3, Azure Blob, and GCP Cloud Storage.
You can use the "External Table" type to point to a data lake that is not housed in the Snowflake environment but allows you to perform compute read-only in the Snowflake environment.
When using Snowpipe to load data into Snowflake you can use serverless computing, which reduces cost as data warehouses are not required.

Wish everyone a very Happy and prosperous Diwali