Data thinking (original) (raw)
Recent years have seen the integration of computer science, mathematics and statistics, together with real-world domain knowledge, into a new research and applications field: data science. Just as data science integrates knowledge and skills from computer science, statistics, and a real-world application domain, data thinking integrates computational thinking, statistical thinking, and domain thinking.
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| dbo:abstract | Recent years have seen the integration of computer science, mathematics and statistics, together with real-world domain knowledge, into a new research and applications field: data science. Just as data science integrates knowledge and skills from computer science, statistics, and a real-world application domain, data thinking integrates computational thinking, statistical thinking, and domain thinking. In the context of new product development and innovation data thinking can be described as follows: Data thinking is a framework to explore, design, develop and validate data-driven solutions and user, data and future-focused businesses. Data thinking combines data science with design thinking and therefore, the focus of this approach does not lie only on data analytics technologies and data collection but also on the design of use-centered solutions with high business potential. The term was created by Mario Faria and Rogerio Panigassi in 2013 when they were writing a book about data science, data analytics, data management and how data practitioners were able to achieve their goals. (en) |
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| dbo:wikiPageWikiLink | dbr:Design_thinking dbr:Coolhunting dbr:Cost–benefit_analysis dbr:Persona dbr:Proof_of_concept dbc:Product_development dbr:Buzzword dbc:Innovation dbr:Data_analysis dbr:Data_management dbr:Data_science dbc:Business_intelligence dbc:Data_management dbc:Applied_data_mining dbr:Business_case dbr:Technology_forecasting dbr:CRISP-DM dbr:Customer_journey |
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| dcterms:subject | dbc:Product_development dbc:Innovation dbc:Business_intelligence dbc:Data_management dbc:Applied_data_mining |
| rdfs:comment | Recent years have seen the integration of computer science, mathematics and statistics, together with real-world domain knowledge, into a new research and applications field: data science. Just as data science integrates knowledge and skills from computer science, statistics, and a real-world application domain, data thinking integrates computational thinking, statistical thinking, and domain thinking. (en) |
| rdfs:label | Data thinking (en) |
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