Apa iku normalisasi basis data?

Question

Accepted Answer

**Normalisasi** yaiku proses ngatur data kanggo **nyuda redundansi** lan nambah integritas kanthi mbagi data menyang tabel-tabel sing ana hubungane, ngetutake serangkaian "bentuk normal." Tujuane: saben piranti data disimpen **sapisan**, ngilangi duplikasi lan anomali sing ditimbulake.

## Masalahe: tabel sing ora dinormalisasi (redundan)

Problems (anomalies):
  ✗ UPDATE anomaly — change Ann's email → must update EVERY one of her orders
  ✗ INSERT anomaly — can't add a customer without an order
  ✗ DELETE anomaly — deleting Ann's last order loses her info entirely
  ✗ Wasted storage and inconsistency risk
```

## Solusi: mbagi menyang tabel-tabel sing ana hubungane

Normalisasi mbagi data supaya saben fakta ana ing sawijining panggonan — info pelanggan ing `customers`, produk ing `products`, lan `orders` ngrujuk menyang dheweke kanthi key.

## Bentuk-bentuk normal (makin ketat)

```text
1NF → atomic values (no repeating groups / multi-valued columns), a primary key
2NF → 1NF + no partial dependency (non-key columns depend on the WHOLE primary key)
3NF → 2NF + no transitive dependency (non-key columns depend ONLY on the key, not
      on other non-key columns)
→ 3NF is the common practical target; BCNF, 4NF, 5NF exist for stricter cases.
```

## Normalisasi versus denormalisasi (tukar-tikar)

```text
Normalized   → less redundancy, better integrity, but more JOINs (can be slower reads)
Denormalized → some duplication for FEWER joins → faster reads (e.g. analytics/reporting)
→ Normalize by default (integrity); selectively denormalize for read performance
  where justified (with care to keep duplicates consistent).
```

## Apa dene pentinge

Normalisasi yaiku konsep dasar desain basis data — iku cara sampeyan nstruktur data kanggo ngilangi redundansi lan njaga integritas, sing mbutuhake kanggo ndesain basis data relasional sing dipercaya, dadi ngerti babagan iki penting.

Nilai inti yaiku nyegah **anomali** sing ditimbulake data redundan (ora dinormalisasi): **update anomali** (ngobah data sing diduplikat ing akeh panggonan, kapengaruhe konsistensi), **insert anomali** (ora bisa nambah data tanpa data sing ora ana hubungane), lan **delete anomali** (ilang data nalika mbusak rekord sing ana hubungane) — kabeh iki nyebabake data sing ora konsisten lan rusak.
\'Kanthi mbagi data menyang tabel-tabel sing ana hubungane supaya saben fakta disimpen sapisan, normalisasi ngilangi masalah iki lan njamin konsistensi data.

Ngerti babagan **bentuk normal** (utamane 1NF, 2NF, lan **3NF** — target praktis sing umum — lan prinsipe yen kolom non-key kudu gumantung ing key) nyedhiyakake kerangka kanggo desain sing bener.

Samakober penting yaiku ngerti babagan **tukar-tikar normalisasi versus denormalisasi**: normalisasi nambah integritas nanging mbutuhake JOINs luwih akeh (bisa-bisa lambat nalika maca), dadi sajrone sampeyan normal kanthi standar kanggo integritas, denormalisasi selektif (tanggap sethithik duplikasi kanggo JOIN sing luwih sethithik lan maca sing luwih cepet) kadhangkala diyakini kanggo performance (contone analytics) — ngerti kapan lan napa nggawekake tukar-tikar iki nggambarake pertimbangan desain sing dewasa.

Mawon modele data sing bener yaiku dhasar kanggo basis data sing dipercaya, lan amarga ngerti normalisasi (ngilangi redundansi lan anomali) lan tukar-tikarane karo denormalisasi (integritas versus performance maca) yaiku kunci kanggo ndesain basis data sing terstruktur apik, konsisten, lan performan, normalisasi yaiku ilmu sing penting lan dhasar kanggo desain basis data lan topik wawancara sing umum sing nuduhake pemahaman babagan modele data sing bener.