The Modern Data Track is heavily inspired by In the End (Linkin Park) and Take A Look Around (Limp Bizkit) — not just the music but also the words.

Here’s the karaoke-ready instrumental soundtrack:

And below are the lyrics with timestamps. I enjoy them more with the soundtrack, hope you do the same!

[From 0:13]

It starts with..

Ingestion, from a data source,
To a destination, where the data goes.
Your website or app is your first-party source,
Every API or SaaS is a third-party source.

All I know..

Data is a valuable thing,
Watch it fly by and face vendor lock-in.
Story a copy so when there is a need,
You’ve got access, you don't need to plead.

[9-second pause]

🎵🎵🎵🎵

[From 0:40]

The Modern Data Stack is no secret,
You need data, so you need tools to collect it, store it, analyze it, and activate it.
It's kinda sad that it seems so complicated,
Alright alright, lemme try and explain it..

The separation of Compute and Storage in the cloud,
Made warehousing cheaper, more accessible, much faster.
Queries take seconds to process in parallel,
Pay as you go, storage is infinitely scalable.

ETL became ELT
Because Extracting and Loading without Transforming is easy,
Once in the warehouse, whenever the need be,
Data can be transformed by writing a SQL query.

Once transformed, your data models are ready,
To derive insights, they need to be visualized,
To drive action, they need to be synchronized,
And that is all, the MDS isn't so complicated after all.

[10-second pause]

🎵🎵🎵🎵

[From 1:28 — slow down]

S-Q-L can get you far,
But if you don't know SQL, it doesn't even matter.
Modern data tools can do it all,
It's early days, they're already getting better.

Ingestion, from a data source,
To a destination, where the data goes.
CDI for your first-party source,
ELT for every third-party source.

It's not so hard..

Warehouse the data, you now know why,
You gotta know where your data lies.
When it's time to derive insights,
Go build them models — analyze and visualize!

But insights alone are not enough.
You gotta take action, it's not so tough.
Reverse ETL or CDP?
It doesn't matter, choose whatever's easy.

[Don’t pause, it gets faster]

I know why you lookin' at me.
I know why you lookin' at me.
Now I know why you lookin' at me.

You wanna know about — Data Quality,
And you want to know about — Observability,
Metrics — Repository,
Cataloging — and Discovery.

[2-second pause]
[From 2:32 — slow down]

Well I would say, don't worry,
Just start small, there's no hurry,
The perfect stack
Is no good if used by nobody-eeee.

[From 2:53]

Data tools, you can buy them all,
But in the end, people are what matter.
Data people and non-data people,
Let's beat the gap, let's do it together-rrrrr!

🎵🎵🎵🎵

Continue Learning

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ELT vs Reverse ETL: An Architectural Overview

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6 months ago · 1 like · Arun Thulasidharan and Arpit Choudhury