The Patterns, Performances, and Challenges of the Big Data Development in Taiwan: Multiple Experts’ Perspectives
台灣大數據由政府推動至今已十餘年，但大數據的發展對許多企業而言仍相當模糊。本研究採用三角定錨法，訪談推動大數據的法人機構、應用公司、數據分析商，共6 位相關專業人士，進行每位約60 分鐘的半結構式訪談，以分析大數據發展現況。訪談資料經歸納取向的質性內容分析法，發現台灣大數據的發展可分為「資料型態」、「分析類型」、「應用與成效」、「環境趨勢」及「挑戰」等五個主要類別。資料型態包含數字、文字／圖像、影音等次類別；分析類型包含數位（足跡）、社群、語意、決策等次類別；應用與成效包含顧客關係管理強化、決策支援優化、成本效益等次類別；環境趨勢包含通路／媒體、概念演化、產業涵蓋、產業集中度、技術平台、法人的合作關係等次類別；最後，挑戰則包含人才需跨領域整合、效益不清／缺乏願景等兩個次類別。
Big data in Taiwan began to be promoted by the government for more than ten years now, but the status, future trend, and limitations are still under mist. Triangulation data resources were used in this study, 6 semi-structured interviews for about 60 minutes each of big data-related professionals from juristic person institutions, application companies, and data analysis agents were collected. Based on the results of the inductive approach by qualitative content analysis, findings revealed five categories of big data development in Taiwan were proposed. Big data types, analysis patterns, application and performance, environmental trends, and challenges are the five categories in this framework. Three main big data types are emerging; they are basic numbers, texts/figures, and high-level audio and video. As to the analysis patterns, many varieties of analysis techniques are applied, including a digital (footprint), the social media community, semantics, and decision analysis. For the application and performance categories, customer relationship management enhancements, decision support optimization, and cost-benefit effectiveness are included. The environmental trends are channels/media, conceptual evolution, industries scopes and concentration, technical platforms, and cooperative with legal foundation. Finally, challenges categories, the need for talent in cross-domain integration, unclear benefits/lack of vision.