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Describe the stages of the ETL data integration model
If I could change how it's written, I would say
ELT, as in you Extract Data from a database or website (Kaggle.com) and then Load it into Excel or another program and then Transform it. Sometimes, you will then Export it and Load it into another (database) or program.
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ETL data integration model:
Extract
Transform
Load
The ETL (Extract, Transform, Load) process is a lot like organizing a big school event, where you have to collect various items (data), prepare or decorate them (transform), and then put everything in place (load) before the event starts. Let's break down each stage:
Extract
Extract
What It Is: This is the first stage where you gather or "extract" data from multiple sources. Think of it like collecting all the props, food, and materials from different places for your school event.
How to Do It:
Identify Sources: Find out where your data is coming from. It could be databases, Excel spreadsheets, or external APIs.
Data Retrieval: Use queries or API calls to pull the data out.
Initial Filtering: Even at this stage, you might do some basic filtering to only collect the data you actually need.
Transform
Transform
What It Is: Now that you have all the materials, you need to prepare or "transform" them to suit your needs. Maybe you need to paint some props or cook the food.
How to Do It:
Data Cleaning: Remove any inconsistencies, duplicates, or errors in the data.
Data Formatting: Convert the data into a common format. For example, if you have date information in different formats, you'll want to standardize it.
Data Enrichment: Add more details or combine data fields to create new information that's more useful. Like adding decorative elements to your props to make them look better.
Data Aggregation: Sometimes, you may need to summarize detailed data into broader categories.
Load
Load
What It Is: Finally, you place everything in the venue or "load" the data into the target database or warehouse so it can be easily accessed and analyzed.
How to Do It:
Target Identification: Decide where the data will be loaded. This could be a relational database, a data warehouse, or even a cloud storage service.
Loading Strategy: You can do a bulk load (putting everything in place at once), or incremental loads (adding new things little by little).
Data Insertion: Physically insert the data into the target destination.
Verification: After loading, it's good to run some checks to make sure everything arrived intact, just like you'd double-check all the setups before the event starts.
And there you go! Just like organizing a successful event, ETL helps you gather, prepare, and place your data where it can be most useful.
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