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Recognize and eliminate barriers to delivering data to users at scale
Work on the right things for the right stakeholders through agile collaboration
Create trust in data via rigorous testing and effective data management
Build a culture of learning and continuous improvement through monitoring deployments and measuring outcomes
Create cross-functional self-organizing teams focused on goals not reporting lines
Build robust, trustworthy, data pipelines in support of AI, machine learning, and other analytical data products
Recognize and eliminate barriers to delivering data to users at scale
Work on the right things for the right stakeholders through agile collaboration
Create trust in data via rigorous testing and effective data management
Build a culture of learning and continuous improvement through monitoring deployments and measuring outcomes
Create cross-functional self-organizing teams focused on goals not reporting lines
Build robust, trustworthy, data pipelines in support of AI, machine learning, and other analytical data products
Introduces a new method to increase value from data science and machine learning
Helps you get past challenges, barriers, and bottlenecks to create value from data
Guides you in choices for prioritizing analytical work, adopting ways of working, choosing technology, and organizing teams
Part I. Getting Started.- 1. The Problem with Data Science.- 2. Data Strategy.- Part II. Toward DataOps.- 3. Lean Thinking.- 4. Agile Collaboration.- 5. Build Feedback and Measurement.- Part III. Further Steps.- 6. Building Trust.- 7. DevOps for DataOps.- 8. Organizing for DataOps.- Part IV. The Self-Service Organization.- 9. DataOps Technology.- 10. The DataOps Factory.
Erscheinungsjahr: | 2019 |
---|---|
Genre: | Importe, Informatik |
Rubrik: | Naturwissenschaften & Technik |
Medium: | Taschenbuch |
Inhalt: |
xxviii
275 S. 43 s/w Illustr. 275 p. 43 illus. |
ISBN-13: | 9781484251034 |
ISBN-10: | 1484251032 |
Sprache: | Englisch |
Ausstattung / Beilage: | Paperback |
Einband: | Kartoniert / Broschiert |
Autor: | Atwal, Harvinder |
Auflage: | 1st ed. |
Hersteller: |
Apress
Apress L.P. |
Verantwortliche Person für die EU: | Books on Demand GmbH, In de Tarpen 42, D-22848 Norderstedt, info@bod.de |
Maße: | 254 x 178 x 17 mm |
Von/Mit: | Harvinder Atwal |
Erscheinungsdatum: | 10.12.2019 |
Gewicht: | 0,576 kg |
Introduces a new method to increase value from data science and machine learning
Helps you get past challenges, barriers, and bottlenecks to create value from data
Guides you in choices for prioritizing analytical work, adopting ways of working, choosing technology, and organizing teams
Part I. Getting Started.- 1. The Problem with Data Science.- 2. Data Strategy.- Part II. Toward DataOps.- 3. Lean Thinking.- 4. Agile Collaboration.- 5. Build Feedback and Measurement.- Part III. Further Steps.- 6. Building Trust.- 7. DevOps for DataOps.- 8. Organizing for DataOps.- Part IV. The Self-Service Organization.- 9. DataOps Technology.- 10. The DataOps Factory.
Erscheinungsjahr: | 2019 |
---|---|
Genre: | Importe, Informatik |
Rubrik: | Naturwissenschaften & Technik |
Medium: | Taschenbuch |
Inhalt: |
xxviii
275 S. 43 s/w Illustr. 275 p. 43 illus. |
ISBN-13: | 9781484251034 |
ISBN-10: | 1484251032 |
Sprache: | Englisch |
Ausstattung / Beilage: | Paperback |
Einband: | Kartoniert / Broschiert |
Autor: | Atwal, Harvinder |
Auflage: | 1st ed. |
Hersteller: |
Apress
Apress L.P. |
Verantwortliche Person für die EU: | Books on Demand GmbH, In de Tarpen 42, D-22848 Norderstedt, info@bod.de |
Maße: | 254 x 178 x 17 mm |
Von/Mit: | Harvinder Atwal |
Erscheinungsdatum: | 10.12.2019 |
Gewicht: | 0,576 kg |