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The Signal Lab
/sql-analysis-practical-034

SQL Analysis — Checklist

DATA & ANALYTICS / DAT-0034

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Act as a data analyst. Buat sql analysis menggunakan data berikut: [PASTE DATA / TABLE / METRICS]. Business context: creator economy. Objective: save time. Audience: beginner. Output: checklist, casual BM. Fokus variasi: practical examples. Semak data quality dahulu, nyatakan missing values/bias/limitations, kemudian cari pattern, outlier, drivers dan actionable insights. Jangan cipta angka yang tiada dalam data.

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Act as a data analyst. Buat sql analysis menggunakan data berikut: [PASTE DATA / TABLE / METRICS]. Business context: creator economy. Objective: save time. Audience: beginner. Output: checklist, casual BM. Fokus variasi: practical examples. Semak data quality dahulu, nyatakan missing values/bias/limitations, kemudian cari pattern, outlier, drivers dan actionable insights. Jangan cipta angka yang tiada dalam data.
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Nearby knowledge

/content-performance-mobile-001

Content Performance — Checklist

Act as a data analyst. Buat content performance menggunakan data berikut: [PASTE DATA / TABLE / METRICS]. Business context: B2B context. Objective: save time. Audience: beginner. Output: checklist, concise. Fokus variasi: mobile-first execution. Semak data quality dahulu, nyatakan missing values/bias/limitations, kemudian cari pattern, outlier, drivers dan actionable insights. Jangan cipta angka yang tiada dalam data.

ChatGPTGeminiClaude+1
/viral-potential-conversion-002

Viral Potential — Checklist

Act as a data analyst. Buat viral potential menggunakan data berikut: [PASTE DATA / TABLE / METRICS]. Business context: B2B context. Objective: save time. Audience: beginner. Output: checklist, concise. Fokus variasi: conversion. Semak data quality dahulu, nyatakan missing values/bias/limitations, kemudian cari pattern, outlier, drivers dan actionable insights. Jangan cipta angka yang tiada dalam data.

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/screenshot-analysis-clarity-003

Screenshot Analysis — Checklist

Act as a data analyst. Buat screenshot analysis menggunakan data berikut: [PASTE DATA / TABLE / METRICS]. Business context: B2B context. Objective: save time. Audience: beginner. Output: checklist, concise. Fokus variasi: clarity. Semak data quality dahulu, nyatakan missing values/bias/limitations, kemudian cari pattern, outlier, drivers dan actionable insights. Jangan cipta angka yang tiada dalam data.

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