Riset Pasar 2 Juta Data

@mobimubasir

Saya bisa kumpulkan 2 juta poin data pasar valid dari sumber online terverifikasi, susun rapi ke CSV/Google Sheets dengan sumber + tanggal tiap baris, plus ringkasan 2-3 halaman temuan kunci dan pola. Berpengalaman pakai scraping tools, API publik, dan metode manual terstruktur untuk jaga akurasi 95%+, format konsisten, dan pengiriman sesuai tenggat.

@cuyodigital

* Halo, saya melihat proyek riset pasar 2 juta data Anda. Anda perlu mengumpulkan data harga, pemain utama, tren, volume penjualan dari sumber online terverifikasi, mengorganisir ke CSV atau Google Sheets dengan tautan sumber dan tanggal, serta ringkasan temuan kunci. Saya memiliki 5+ tahun dalam pengumpulan data web scraping dan API, dan lebih dari 20 proyek data besar selesai. Anda dapat melihat contoh di profil saya: https://www.freelancer.com/u/cuyodigital. Deliverables: 2 juta baris data valid dengan akurasi 95%, spreadsheet rapi, ringkasan 2-3 halaman. Harga 20 USD untuk 30 hari. Dua pertanyaan: Sektor pasar apa yang menjadi fokus utama? Apakah Anda memiliki daftar sumber data spesifik atau perlu saya cari sendiri? Beri tahu jawaban Anda. Saya bisa mulai segera. Ricardo PS. Saya memiliki pertanyaan tentang proyek dan saya ingin Anda memeriksa papan klarifikasi

@edgarasspro

This is a large-scale structured data collection task, so the real challenge here is not just volume (2M rows), but maintaining consistency, source traceability, and accuracy across all entries without format drift over time. I understand you need a purely data-gathering workflow: extracting verified market information (prices, key players, trends, volumes, or agreed metrics), structuring it into CSV or Google Sheets, and ensuring every row includes a verifiable source link and timestamp. The final output also includes a short analytical summary highlighting key patterns and anomalies. My approach is to design a scalable data pipeline using a mix of API sources (where available) and controlled scraping with validation layers to ensure consistency. I would define a strict schema first, then automate collection with deduplication, rate-limit handling, and periodic sampling checks to maintain the 95% accuracy target. Data integrity and uniform formatting will be enforced at ingestion level, not post-processing. I’ve worked on structured data extraction pipelines using APIs and scraping frameworks where consistency, validation, and high-volume processing were critical requirements. One question: do you already have the target industry or sectors defined, or should I help refine the data taxonomy and column structure before collection starts? Once aligned, I can propose a realistic timeline and batching strategy for delivering the full 2M dataset reliably.