Building Data Science Teams
As data science evolves to become a business necessity, the importance of assembling a strong and innovative data teams grows. In this in-depth report, data scientist DJ Patil explains the skills,perspectives, tools and processes that position data science teams for success.
| Otros Autores: | |
|---|---|
| Formato: | Libro electrónico |
| Idioma: | Inglés |
| Publicado: |
[Place of publication not identified]
O'Reilly Media Incorporated
2011
|
| Edición: | 1st edition |
| Ver en Biblioteca Universitat Ramon Llull: | https://discovery.url.edu/permalink/34CSUC_URL/1im36ta/alma991009822776906719 |
Tabla de Contenidos:
- Cover
- Aster Data
- Table of Contents
- Building Data Science Teams
- Being Data Driven
- The Roles of a Data Scientist
- Decision sciences and business intelligence
- Product and marketing analytics
- Fraud, abuse, risk and security
- Data services and operations
- Data engineering and infrastructure
- Organizational and reporting alignment
- What Makes a Data Scientist?
- Hiring and talent
- Would we be willing to do a startup with you?
- Can you "knock the socks off" of the company in 90 days?
- In four to six years, will you be doing something amazing?
- Building the LinkedIn Data Science Team
- Reinvention
- About the Author
- O'Reilly Strata.
