Debug School

rakesh kumar
rakesh kumar

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Difference between Datalake and Databrick

What is a Data Lake?
Data Lake vs Database
What is Databricks?
Example with Data Lake + Databricks
Real-World Analogy
Why Not Just Use Database?
Databricks Extra Power
Final Simple Definition

What is a Data Lake?

Simple Meaning:

A Data Lake is a large storage system where you store all types of data in raw form.

Think of it like:

🏞️ A real lake — where water from rivers, rain, streams all flow into one big place.

Same way:

App data

Logs

Images

Videos

CSV files

JSON files
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Database exports
All go into one central storage.

🧱 Key Features of a Data Lake

Stores structured data (tables, Excel, CSV)

Stores semi-structured data (JSON, XML)

Stores unstructured data (images, audio, video)

Data is stored in raw format
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Very scalable (petabytes of data)

🏢 Example

Let’s say you run MyHospitalNow:

You collect:

Patient records

Doctor activity logs

Payment transactions

App click events

Feedback forms

Images & documents
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Instead of storing everything in different systems, you dump all into a Data Lake.

Later:

Data scientist can analyze trends

You can build AI models

You can generate reports
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Data Lake vs Database

What is Databricks?

Now comes the second part.

Simple Meaning:

Databricks is a platform that helps you:

Analyze, process, clean, and build AI models from data stored in a Data Lake.

If Data Lake is storage,

Databricks is the processing & intelligence engine.
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🧠 What Databricks Actually Does

Databricks is built on Apache Spark.

It helps you:

Process big data fast

Clean messy raw data

Run analytics

Build machine learning models

Create dashboards

Manage Data Lake properly
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🏗

Example with Data Lake + Databricks

Let’s continue MyHospitalNow example:

Step 1:

All raw data stored in:

AWS S3

Azure Data Lake

Google Cloud Storage
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(This is your Data Lake)

Step 2:

You use Databricks to:

Clean duplicate patient records

Analyze doctor performance

Predict patient revisit rate

Build AI model for disease prediction

Generate revenue dashboards
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Databricks reads from Data Lake → processes data → gives insights.

Real-World Analogy

Why Not Just Use Database?

Because:

Database cannot handle petabytes easily

AI models need raw historical data

Logs and media files cannot fit into normal SQL

🧠

Databricks Extra Power

Databricks also provides:

Delta Lake (improved version of Data Lake with ACID transactions)

Notebooks for collaboration

Auto-scaling clusters

Real-time streaming processing

AI & ML tools built-in

🎯

Final Simple Definition

✅ Data Lake:

A central place to store all raw data at large scale.
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✅ Databricks:

A platform to process, analyze, and build AI models from Data Lake data.
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