The decision maker's handbook to data science: a guide for non-technical executives, managers, and founders
Data science is expanding across industries at a rapid pace, and the companies first to adopt best practices will gain a significant advantage. To reap the benefits, decision makers need to have a confident understanding of data science and its application in their organization. It is easy for novic...
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Buch |
| Sprache: | English |
| Veröffentlicht: |
[Berkeley, California]
Apress
[2020]
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| Ausgabe: | Second edition |
| Schlagworte: | |
| Zusammenfassung: | Data science is expanding across industries at a rapid pace, and the companies first to adopt best practices will gain a significant advantage. To reap the benefits, decision makers need to have a confident understanding of data science and its application in their organization. It is easy for novices to the subject to feel paralyzed by intimidating buzzwords, but what many dont realize is that data science is in fact quite multidisciplinary--useful in the hands of business analysts, communications strategists, designers, and more. With the second edition of The Decision Makers Handbook to Data Science, you will learn how to think like a veteran data scientist and approach solutions to business problems in an entirely new way. Author Stylianos Kampakis provides you with the expertise and tools required to develop a solid data strategy that is continuously effective. Ethics and legal issues surrounding data collection and algorithmic bias are some common pitfalls that Kampakis helps you avoid, while guiding you on the path to build a thriving data science culture at your organization. This updated and revised second edition, includes plenty of case studies, tools for project assessment, and expanded content for hiring and managing data scientists Data science is a language that everyone at a modern company should understand across departments. Friction in communication arises most often when management does not connect with what a data scientist is doing or how impactful data collection and storage can be for their organization. The Decision Makers Handbook to Data Science bridges this gap and readies you for both the present and future of your workplace in this engaging, comprehensive guide |
| Beschreibung: | viii, 156 pages illustrations 24 cm |
| ISBN: | 1484254937 9781484254936 |
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| 505 | 8 | |a Demystifying data science and all the other buzzwords -- Data management -- Data collection problems -- How to keep data tidy -- Thinking like a data scientist (without being one) -- A short introduction to statistics -- A short introduction to machine learning -- Problem solving -- Pitfalls -- Hiring and managing data scientists -- Building a data science culture -- Data science rules the world -- Tools for data science | |
| 520 | 3 | |a Data science is expanding across industries at a rapid pace, and the companies first to adopt best practices will gain a significant advantage. To reap the benefits, decision makers need to have a confident understanding of data science and its application in their organization. It is easy for novices to the subject to feel paralyzed by intimidating buzzwords, but what many dont realize is that data science is in fact quite multidisciplinary--useful in the hands of business analysts, communications strategists, designers, and more. With the second edition of The Decision Makers Handbook to Data Science, you will learn how to think like a veteran data scientist and approach solutions to business problems in an entirely new way. Author Stylianos Kampakis provides you with the expertise and tools required to develop a solid data strategy that is continuously effective. Ethics and legal issues surrounding data collection and algorithmic bias are some common pitfalls that Kampakis helps you avoid, while guiding you on the path to build a thriving data science culture at your organization. This updated and revised second edition, includes plenty of case studies, tools for project assessment, and expanded content for hiring and managing data scientists Data science is a language that everyone at a modern company should understand across departments. Friction in communication arises most often when management does not connect with what a data scientist is doing or how impactful data collection and storage can be for their organization. The Decision Makers Handbook to Data Science bridges this gap and readies you for both the present and future of your workplace in this engaging, comprehensive guide | |
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| contents | Demystifying data science and all the other buzzwords -- Data management -- Data collection problems -- How to keep data tidy -- Thinking like a data scientist (without being one) -- A short introduction to statistics -- A short introduction to machine learning -- Problem solving -- Pitfalls -- Hiring and managing data scientists -- Building a data science culture -- Data science rules the world -- Tools for data science |
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| spelling | Kampakis, Stylianos Verfasser (DE-588)1203406231 aut The decision maker's handbook to data science a guide for non-technical executives, managers, and founders Stylianos Kampakis Second edition [Berkeley, California] Apress [2020] viii, 156 pages illustrations 24 cm txt rdacontent n rdamedia nc rdacarrier Demystifying data science and all the other buzzwords -- Data management -- Data collection problems -- How to keep data tidy -- Thinking like a data scientist (without being one) -- A short introduction to statistics -- A short introduction to machine learning -- Problem solving -- Pitfalls -- Hiring and managing data scientists -- Building a data science culture -- Data science rules the world -- Tools for data science Data science is expanding across industries at a rapid pace, and the companies first to adopt best practices will gain a significant advantage. To reap the benefits, decision makers need to have a confident understanding of data science and its application in their organization. It is easy for novices to the subject to feel paralyzed by intimidating buzzwords, but what many dont realize is that data science is in fact quite multidisciplinary--useful in the hands of business analysts, communications strategists, designers, and more. With the second edition of The Decision Makers Handbook to Data Science, you will learn how to think like a veteran data scientist and approach solutions to business problems in an entirely new way. Author Stylianos Kampakis provides you with the expertise and tools required to develop a solid data strategy that is continuously effective. Ethics and legal issues surrounding data collection and algorithmic bias are some common pitfalls that Kampakis helps you avoid, while guiding you on the path to build a thriving data science culture at your organization. This updated and revised second edition, includes plenty of case studies, tools for project assessment, and expanded content for hiring and managing data scientists Data science is a language that everyone at a modern company should understand across departments. Friction in communication arises most often when management does not connect with what a data scientist is doing or how impactful data collection and storage can be for their organization. The Decision Makers Handbook to Data Science bridges this gap and readies you for both the present and future of your workplace in this engaging, comprehensive guide Big Data (DE-588)4802620-7 gnd rswk-swf Datenanalyse (DE-588)4123037-1 gnd rswk-swf Data Mining (DE-588)4428654-5 gnd rswk-swf Decision making / Data processing Big data Database management Data Mining (DE-588)4428654-5 s Big Data (DE-588)4802620-7 s Datenanalyse (DE-588)4123037-1 s 1\p DE-604 1\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk |
| spellingShingle | Kampakis, Stylianos The decision maker's handbook to data science a guide for non-technical executives, managers, and founders Demystifying data science and all the other buzzwords -- Data management -- Data collection problems -- How to keep data tidy -- Thinking like a data scientist (without being one) -- A short introduction to statistics -- A short introduction to machine learning -- Problem solving -- Pitfalls -- Hiring and managing data scientists -- Building a data science culture -- Data science rules the world -- Tools for data science Big Data (DE-588)4802620-7 gnd Datenanalyse (DE-588)4123037-1 gnd Data Mining (DE-588)4428654-5 gnd |
| subject_GND | (DE-588)4802620-7 (DE-588)4123037-1 (DE-588)4428654-5 |
| title | The decision maker's handbook to data science a guide for non-technical executives, managers, and founders |
| title_auth | The decision maker's handbook to data science a guide for non-technical executives, managers, and founders |
| title_exact_search | The decision maker's handbook to data science a guide for non-technical executives, managers, and founders |
| title_exact_search_txtP | The decision maker's handbook to data science a guide for non-technical executives, managers, and founders |
| title_full | The decision maker's handbook to data science a guide for non-technical executives, managers, and founders Stylianos Kampakis |
| title_fullStr | The decision maker's handbook to data science a guide for non-technical executives, managers, and founders Stylianos Kampakis |
| title_full_unstemmed | The decision maker's handbook to data science a guide for non-technical executives, managers, and founders Stylianos Kampakis |
| title_short | The decision maker's handbook to data science |
| title_sort | the decision maker s handbook to data science a guide for non technical executives managers and founders |
| title_sub | a guide for non-technical executives, managers, and founders |
| topic | Big Data (DE-588)4802620-7 gnd Datenanalyse (DE-588)4123037-1 gnd Data Mining (DE-588)4428654-5 gnd |
| topic_facet | Big Data Datenanalyse Data Mining |
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