Multidimensional Data Visualization

數位化的發展，對環境、社會及企業治理帶來了極大的衝擊，其中，大數據、雲端運算、人工智慧（AI）等新技術正在對會計領域產生重大影響。於此之際，美國會計師（AICPA）考試藍圖內容也跟著部分變更，改變方針強調新技術對會計的影響，未來執業的會計師更需要瞭解企業的業務，包括業務流程、資訊系統、資料流向、財務業務風險和相關的內部控制。另一方面，數據治理（Data Governance）日益重要，善用AI 以協助或增強人類的決策能力，也是未來趨勢。會計教育的挑戰不僅是傳授國際財務報導準則（IFRSs）、審計等專業知識，基礎領域，更包括數位思維（Digital mindset）和數據分析的養成，以及對企業組織中的系統和組織控制機制的瞭解。也就是說，隨著業務流程的自動化，學習會計不再是加強計算，而是更強調理解和應用概念。在數據分析方面，學習會計能夠更有效地使用新技術和新的數據來源，提升工作效率。面對企業將 IT 外包、將資料存儲在雲端，學習會計可以理解會計師如何對財報或內部控制的評估，此外，遠距工作對查核實務的影響，也可以從學習會計一窺堂奧。________________________________________相較於前一版的內容，本版增訂部分僅說明如下：• 配合國際會計準則，修改各章相關文字內容，提升企業會計資訊透明度。• 新增會計思維和數據分析的概念。• 加強「本期綜合損益＝本期損益＋其他綜合損益」之關聯性。• 為讓初次學習者對「綜合損益表」有完整概念，本書前五章，於編製綜合損益表時，除列示本期損益外，並列示「其他綜合損益$0」，以完整呈現綜合損益表之樣態。• 配合國際會計準則之修正，更新「流動資產」與「流動負債」之定義。• 更新IFRS 15「客戶合約之收入」觀念。• 配合IFRS 9、15 修改應收款項與投資。• 新增IAS 37 負債準備及或有負債主題，豐富會計主題。• 更新日常經濟活動與公報相關實例，協助學習者瞭解會計與商業活動的關聯性。• 更新新聞短訊，呈現時下企業實務運作情況。• 新增部分題庫，提供更新學習成果考核依據。

產品特色： 1.採用Microsoft 微軟所推出Power BI 軟體結合Excel 應用工具，透過步驟化的教學與說明，讓跨領域者與商業數據分析應用技能相互整合。 2.本書囊括資料清理到應用與視覺化分析等專業知識建構，一應俱全。 3.本書適合對商業智慧跨領域學習感興趣的學習者、學術機構與訓練中心採用，讓學生體驗跨領域職能的整合應用、商業智慧基礎應用、視覺化圖表製作等技術與核心知識建置技能實務操作

All social and policy researchers need to synthesize data into a visual representation. Producing good visualizations combines creativity and technique. This book teaches the techniques and basics to produce a variety of visualizations, allowing readers to communicate data and analyses in a creative and effective way. Visuals for tables, time series, maps, text, and networks are carefully explained and organized, showing how to choose the right plot for the type of data being analysed and displayed. Examples are drawn from public policy, public safety, education, political tweets, and public health. The presentation proceeds step by step, starting from the basics, in the programming languages R and Python so that readers learn the coding skills while simultaneously becoming familiar with the advantages and disadvantages of each visualization. No prior knowledge of either Python or R is required. Code for all the visualizations are available from the book's website.

All social and policy researchers need to synthesize data into a visual representation. Producing good visualizations combines creativity and technique. This book teaches the techniques and basics to produce a variety of visualizations, allowing readers to communicate data and analyses in a creative and effective way. Visuals for tables, time series, maps, text, and networks are carefully explained and organized, showing how to choose the right plot for the type of data being analysed and displayed. Examples are drawn from public policy, public safety, education, political tweets, and public health. The presentation proceeds step by step, starting from the basics, in the programming languages R and Python so that readers learn the coding skills while simultaneously becoming familiar with the advantages and disadvantages of each visualization. No prior knowledge of either Python or R is required. Code for all the visualizations are available from the book's website.

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