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ETL vs ELT โ€“ Explained Using Apple Juice analogy! ๐ŸŽ๐Ÿงƒ

We often hear about ETL and ELT in the data world โ€” but how do they actually apply in tools like Excel and Power BI?

Letโ€™s break it down with a simple and relatable analogy ๐Ÿ‘‡

โœ… ETL (Extract โ†’ Transform โ†’ Load)

๐Ÿงƒ First you make the juice, then you deliver it

โžก๏ธ Apples โ†’ Juice โ†’ Truck

๐Ÿ”น In Power BI / Excel:

You clean and transform the data in Power Query
Then load the final data into your report or sheet
๐Ÿ’ก Thatโ€™s ETL โ€“ transformation happens before loading



โœ… ELT (Extract โ†’ Load โ†’ Transform)

๐Ÿ First you deliver the apples, and make juice later

โžก๏ธ Apples โ†’ Truck โ†’ Juice

๐Ÿ”น In Power BI / Excel:

You load raw data into your model or sheet
Then transform it using DAX, formulas, or pivot tables
๐Ÿ’ก Thatโ€™s ELT โ€“ transformation happens after loading
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๐—”๐—ฐ๐—ฒ ๐—ฌ๐—ผ๐˜‚๐—ฟ ๐—ฆ๐—ค๐—Ÿ ๐—œ๐—ป๐˜๐—ฒ๐—ฟ๐˜ƒ๐—ถ๐—ฒ๐˜„ ๐˜„๐—ถ๐˜๐—ต ๐—ง๐—ต๐—ฒ๐˜€๐—ฒ ๐Ÿฏ๐Ÿฌ ๐— ๐—ผ๐˜€๐˜-๐—”๐˜€๐—ธ๐—ฒ๐—ฑ ๐—ค๐˜‚๐—ฒ๐˜€๐˜๐—ถ๐—ผ๐—ป๐˜€! ๐Ÿ˜

๐Ÿคฆ๐Ÿปโ€โ™€๏ธStruggling with SQL interviews? Not anymore!๐Ÿ“

SQL interviews can be challenging, but preparation is the key to success. Whether youโ€™re aiming for a data analytics role or just brushing up, this resource has got your back!๐ŸŽŠ

๐‹๐ข๐ง๐ค๐Ÿ‘‡:-

https://pdlink.in/4olhd6z

Letโ€™s crack that interview together!โœ…๏ธ
โค1
Understand the power of Data Lakehouse Architecture for ๐—™๐—ฅ๐—˜๐—˜ here...


๐Ÿšจ๐—ข๐—น๐—ฑ ๐˜„๐—ฎ๐˜†
โ€ข Complicated ETL processes for data integration.
โ€ข Silos of data storage, separating structured and unstructured data.
โ€ข High data storage and management costs in traditional warehouses.
โ€ข Limited scalability and delayed access to real-time insights.

โœ…๐—ก๐—ฒ๐˜„ ๐—ช๐—ฎ๐˜†
โ€ข Streamlined data ingestion and processing with integrated SQL capabilities.
โ€ข Unified storage layer accommodating both structured and unstructured data.
โ€ข Cost-effective storage by combining benefits of data lakes and warehouses.
โ€ข Real-time analytics and high-performance queries with SQL integration.

The shift?

Unified Analytics and Real-Time Insights > Siloed and Delayed Data Processing

Leveraging SQL to manage data in a data lakehouse architecture transforms how businesses handle data.

Data Engineering Interview Preparation Resources: https://whatsapp.com/channel/0029Vaovs0ZKbYMKXvKRYi3C

All the best ๐Ÿ‘๐Ÿ‘
โค1