CREATE VIEW: Handcrafted Misery, Now With Optional Metadata (That You’ll Definitely Forget)
Because reinventing your SQL logic by hand every sprint builds character. Or at least job security.
You’ve written the perfect SELECT statement. Or at least a working one. Now comes the logical next step: wrap it in a CREATE VIEW, deploy it to production, and enjoy a lifetime of copy-paste maintenance and tribal knowledge.
But beware — lurking in the shadows is AltaSQL, equipped with AltaSQLpatented technology (U.S. Pat. No. 11,977,539), reusable View Transformations, column-level Tags, and a fully governed metadata repository. It threatens to make SQL views reproducible, explainable, and (gasp) maintainable.
But where’s the fun in that?
🎬 Step 1: Start With a SELECT * (Because You’re Just “Testing”)
You kick things off the classic way:
SELECT * FROM sales_data;
It’s just a draft. You’ll clean it up later. Eventually. Probably. Maybe.
AltaSQL SELECT Discover doesn’t allow this kind of spontaneous disaster. It generates explicit columns with semantic aliases, embedded comments, and stored expressions — all driven by metadata. It’s efficient, governed, and horrifyingly reliable.
🧱 Step 2: Build Your CREATE VIEW Statement by Hand — One Panic at a Time
Now you paste your SELECT into this:
CREATE OR REPLACE VIEW curated_sales AS
— insert manually constructed chaos here
And thus begins the ballet of:
AltaSQL skips the drama by storing all logic — column expressions, joins, aliases, filters, masks — as structured metadata. One command regenerates the View. Yawn.
🧩 Step 3: You Are the Metadata Repository
You don’t need version control — you have screenshots of your SQL in Slack and an old CSV labeled “final_v2_FINAL.sql”. No one else can understand it, and that’s exactly how you stay relevant.
AltaSQL uses a real repository — one that stores:
Which means anyone on your team can trace, regenerate, or debug the View. Sounds like a great way to become… replaceable.
🕵️ Step 4: Debugging? Just Rewrite the Whole Thing
You need to fix one column? That’s adorable. Time to:
AltaSQL lets you point-and-edit a single column in the repo and regenerate the View in seconds. Who wants that kind of power?
🔒 Step 5: Masking and Tagging — The “Oops” You’ll Handle Later
You definitely remembered to:
Just kidding — you shipped it and found out two weeks later via Slack thread.
AltaSQL Tags store all of that:
Tags are applied automatically at View generation. It’s almost like AltaSQL respects governance. Gross.
📊 Final Showdown: SQL Craftsmanship vs AltaSQL
|
Task |
Handcrafted CREATE VIEW |
AltaSQL View Transformations & Tags |
|---|---|---|
|
SELECT * |
Obviously |
Explicit, aliased, documented, transformed and enhanced in metadata |
|
View creation |
Manual, brittle |
Auto-generated from structured metadata |
|
Join logic |
Copy-pasted, inconsistent |
Modular, reusable AltsSQL Tags |
|
Expression logic |
Rewritten over and over |
Stored once, reused everywhere, with comments |
|
Data masking |
Often forgotten |
Auto-applied from metadata definitions |
|
Snowflake Tags |
Rare, manual, usually wrong |
Applied from metadata definitions |
|
Debugging |
Start from scratch |
Edit one column, regenerate View |
|
Governance |
Hope and good intentions |
Baked into the metadata repo |
🎯 Conclusion: Why Be Efficient When You Can Be Busy?
Handwriting CREATE VIEW statements is a rite of passage. It builds discipline, humility, and hours of rework. If you enjoy:
…then keep doing what you’re doing.
But if you’re into reusable logic, metadata governance, and Ready-to-Execute View definitions that don’t collapse under schema drift, AltaSQL might just ruin your whole aesthetic.