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    # 從 Side Project 到開源生態:FinMind 的資料工程之路 - 林子軒 Sam {%hackmd o8oUosN0QnqMSkF1_6kH7g %} #### 📚 議程介紹 {%preview https://webconf.tw/agenda/35 %} ###### ▼▼▼ 開始筆記 ▼▼▼ 1. [FinMind 的簡報](https://docs.google.com/presentation/d/1aGaelYX0Ll0XYu1vjx43lVjOxnvBymCWiK0KXNngISM/edit?usp=sharing) 2. [FindMind詳細介紹](https://finmind.github.io/) 3. [FinMind 官網](https://finmindtrade.com/) 4. 想要作資料分析,最直接的作法是加入一間公司,分析其中的資料。若沒有,就要找公開的資料才足夠多用來作分析。股市資料是相對容易取得且量很大的公開資料 如果想要大數據/雲端的經驗,但相關的工作都需要有經驗才能作,那就作 side project 練習,來證明你有大數據/雲端的經驗 # 歷程 2018創立開源、2022開始營利、2024年才損益兩平。 雖然是第4年才開始收費,但在開源免費的前4年,也因此找到工作、出書、創業...。 # 經驗過程 ## 為什麼要做 * 累積「目前接觸不到的領域」的經驗 * 從自身需求 (做專案缺乏Data) → 想到具有類似需求的受眾群 ## 如何找到Side Project題目 * 先不用想能不能盈利,先讓你的產品有人使用。 * 不用怕發想太簡單。(發展到後來就會變深、變廣) * 不需要先變強,才能做 Side Project。 * 需要一個,完美的點子。 * 不用擔心自己做的不好,初期根本沒人知道你。 ## 如何開始 * 從基本能力: 爬蟲。 * 從簡單開始,到社群搜集回饋和成就感(才會知道用戶到痛點在哪裡)。 * 測試市場對這個需求的期待值,搜集到社群的回饋。 * => 可以運行,但如果量大呢?(考慮到需 兼顧系統穩定) * 越多人用越好,盡量通用於不限語言(甚至不需要會程式語言) * 有人使用我的 Data,我才知道真實世界,會遇到什麼問題。 ## 如何節省成本 * 監控系統? 有開源服務 Grafana、Netdata * 網址? 有免費服務 Cloudflare * 雲端 VM? GCP 終身免費提供 e2-micro * 視覺化? 有開源 Superset、Redash * AI ? Gemini 有免費版本 * Open Data? FinMind 免費提供 Open Data ## 如何走向營利 一開始限制流量 (避免Server被打爆) => 開始收到用戶來信 願意付費,獲取更高使用流量 願意付費,希望 FinMind 增加特定資料 願意付費,但需要發票報帳 想要合作客製新功能 ...等 * 參考其他知名的 Open Source 如何營利? Docker、Airflow、MLFlow、Superset、Redis、dbt …etc * 免費提供社群版本,針對雲端託管、進階功能收費 Gemini、ChatGPT 也都提供免費額度 ## 盤點收穫 能力升級 : Junior → Senior ;Engineer → Manager 1. 從0開始 (沒有前人設計好的架構) 1. 自己維運 1. 跟使用者討論需求 1. 控制成本 1. 寫文件 1. 找人才組團隊 1. 專案管理 : 自己設定階段性目標,拆解成小任務 ## 總結 不要侷限自己。 工程師的價值: Coding(x) 解決問題(o)

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