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最新個案
- A practical guide to SEC ï¬nancial reporting and disclosures for successful regulatory crowdfunding
- Quality shareholders versus transient investors: The alarming case of product recalls
- The Health Equity Accelerator at Boston Medical Center
- Monosha Biotech: Growth Challenges of a Social Enterprise Brand
- Assessing the Value of Unifying and De-duplicating Customer Data, Spreadsheet Supplement
- Building an AI First Snack Company: A Hands-on Generative AI Exercise, Data Supplement
- Building an AI First Snack Company: A Hands-on Generative AI Exercise
- Board Director Dilemmas: The Tradeoffs of Board Selection
- Barbie: Reviving a Cultural Icon at Mattel (Abridged)
- Happiness Capital: A Hundred-Year-Old Family Business's Quest to Create Happiness
Data Science and the Art of Persuasion
內容大綱
Despite heavy investments to acquire talented data scientists and take advantage of the analytics boom, many companies have been disappointed in the results. The problem is that those scientists are trained to ask smart questions, wrangle the relevant data, and uncover insights--but not to communicate what those insights mean for the business. To be successful, the author writes, a data science team needs six talents: project management, data wrangling, data analysis, subject expertise, design, and storytelling. He outlines four steps for achieving that success: (1) Define talents, not team members. (2) Hire to create a portfolio of necessary talents. (3) Expose team members to talents they don't have. (4)  Structure projects around talents.