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020 _a9781484262283
040 _dUNAV
_bspa
_cUEV
050 _aHD66
_b.A53 2020 EB
082 0 4 _a005.7
_223
100 1 _aAnderson, Jesse
245 1 0 _aData Teams :
_bA Unified Management Model for Successful Data-Focused Teams
_cby Jesse Anderson
250 _a1st ed
260 _aBerkeley, CA
_bApress
_c2020
300 _a1 recurso en línea (XXIV, 294 p.)
336 _2rdacontent
_aTexto (visual)
_btxt
337 _2rdamedia
_aelectrónico
_bc
338 _2rdacarrier
_arecurso electrónico
_bcr
490 0 _aSpringer eBooks
505 0 _aPart 1: Introducing Data Teams -- Chapter 1: Data Teams -- Chapter 2: The Good, the Bad, and the Ugly Data Teams -- Part 2: Building Your Data Team -- Chapter 3: The Data Science Team -- Chapter 4: The Data Engineering Team -- Chapter 5: The Operations Team -- Chapter 6: Specialized Staff -- Part 3: Working Together and Managing the Data Teams -- Chapter 7: Working as a Data Team -- Chapter 8: How the Business Interacts with Data Teams -- Chapter 9: Managing Big Data Projects -- Chapter 10: Starting a Team -- Chapter 11: The Steps for Successful Big Data Projects -- Chapter 12: Organizational Changes -- Chapter 13: Diagnosing and Fixing Problems -- Part 4: Case Studies and Interviews -- Chapter 14: Interview with Eric Colson and Brad Klingenberg, Stitch Fix -- Chapter 15: Interview with Dmitriy Ryaboy, Twitter, Cloudera, Zymergen -- Chapter 16: Interview with Bas Geerdink, ING, Rabobank -- Chapter 17: Interview with Harvinder Atwal, Moneysupermarket -- Chapter 18: Interview with a Large British Telecommunications Company -- Chapter 19: Interview with Mikio Braun, Zalando.-.
520 _aLearn how to run successful big data projects, how to resource your teams, and how the teams should work with each other to be cost effective. This book introduces the three teams necessary for successful projects, and what each team does. Most organizations fail with big data projects and the failure is almost always blamed on the technologies used. To be successful, organizations need to focus on both technology and management. Making use of data is a team sport. It takes different kinds of people with different skill sets all working together to get things done. In all but the smallest projects, people should be organized into multiple teams to reduce project failure and underperformance. This book focuses on management. A few years ago, there was little to nothing written or talked about on the management of big data projects or teams. Data Teams shows why management failures are at the root of so many project failures and how to proactively prevent such failures with your project. You will: Discover the three teams that you will need to be successful with big data Understand what a data scientist is and what a data science team does Understand what a data engineer is and what a data engineering team does Understand what an operations engineer is and what an operations team does Know how the teams and titles differ and why you need all three teams Recognize the role that the business plays in working with data teams and how the rest of the organization contributes to successful data projects
538 _aForma de acceso: World Wide Web
650 7 _2embne
_914862
_aGrupos de trabajo
710 2 _aSpringerLink
856 4 0 _uhttps://go.openathens.net/redirector/universidadeuropea.es?url=http://doi.org/10.1007/978-1-4842-6228-3
_zAcceso a este recurso digital (usuarios Universidad Europea de Valencia)
942 _2lcc
_cLE
998 _db