@@sanishthomas2858 interesting question. Here is the answer for you: In a Lakehouse, tables are created from data stored in a data lake, supporting both structured and unstructured data with schema-on-read flexibility. They are designed for advanced analytics, machine learning, and big data processing, using technologies like Delta Lake to ensure scalability, ACID transactions, and time-travel features. In a Data Warehouse, tables are highly structured with a predefined schema (schema-on-write). Data warehouses are optimized for business intelligence and complex SQL queries, focusing on performance and consistency. They are best suited for structured data and require more maintenance for schema management. Lakehouses offer more flexibility and scalability, while data warehouses excel at structured data and predefined schemas for business intelligence. PS: Lakehouse is a combination of Data Lake and Data Warehouse. It's a modern approach to handle all the current and future requirements for Data Science (ML, AI etc)
Great news and good information Ajay
Nice. are these playlist good to clear the exams?
Yes, definitely! But you need to practice as well
@@BIConsultingPro quick question, what is the difference between tables in Lakehouse vs tables created in warehouse
@@sanishthomas2858 interesting question. Here is the answer for you:
In a Lakehouse, tables are created from data stored in a data lake, supporting both structured and unstructured data with schema-on-read flexibility. They are designed for advanced analytics, machine learning, and big data processing, using technologies like Delta Lake to ensure scalability, ACID transactions, and time-travel features.
In a Data Warehouse, tables are highly structured with a predefined schema (schema-on-write). Data warehouses are optimized for business intelligence and complex SQL queries, focusing on performance and consistency. They are best suited for structured data and require more maintenance for schema management.
Lakehouses offer more flexibility and scalability, while data warehouses excel at structured data and predefined schemas for business intelligence.
PS: Lakehouse is a combination of Data Lake and Data Warehouse. It's a modern approach to handle all the current and future requirements for Data Science (ML, AI etc)
Thanks man. You are doing great job.
Thank you for the feedback!! Much appreciated :)