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- Data_science abstract "Data science is the study of the generalizable extraction of knowledge from data, yet the key word is science. It incorporates varying elements and builds on techniques and theories from many fields, including signal processing, mathematics, probability models, machine learning, statistical learning, computer programming, data engineering, pattern recognition and learning, visualization, uncertainty modeling, data warehousing, and high performance computing with the goal of extracting meaning from data and creating data products. Data Science is not restricted to only big data, although the fact that data is scaling up makes big data an important aspect of data science.A practitioner of data science is called a data scientist. Data scientists solve complex data problems through employing deep expertise in some scientific discipline. It is generally expected that data scientists are able to work with various elements of mathematics, statistics and computer science, although expertise in these subjects are not required. However, a data scientist is most likely to be an expert in only one or two of these disciplines and proficient in another two or three. This means that data science must be practiced as a team, where across the membership of the team there is expertise and proficiency across all the disciplines.Good data scientists are able to apply their skills to achieve a broad spectrum of end results. Some of these include the ability to find and interpret rich data sources, manage large amounts of data despite hardware, software and bandwidth constraints, merge data sources together, ensure consistency of data-sets, create visualizations to aid in understanding data, build mathematical models using the data, present and communicate the data insights/findings to specialists and scientists in their team and if required to a naive audience. The skill-sets and competencies that data scientists employ vary widely. Data scientists are an integral part of competitive intelligence, a newly emerging field that encompasses a number of activities, such as data mining and analysis, that can help businesses gain a competitive edge.Data science techniques impact how we access data and conduct research across various domains, including the biological sciences, medical informatics, social sciences and the humanities.".
- Data_science thumbnail Data_Science_Venn_Diagram.png?width=300.
- Data_science wikiPageExternalLink dataedge.ischool.berkeley.edu.
- Data_science wikiPageExternalLink Data_Science:_An_Introduction.
- Data_science wikiPageExternalLink icdse.cusat.ac.in.
- Data_science wikiPageExternalLink iwdds.fudan.edu.cn.
- Data_science wikiPageExternalLink teachdatascience.
- Data_science wikiPageExternalLink strataconf.com.
- Data_science wikiPageExternalLink 1449367615.
- Data_science wikiPageExternalLink www.datacurry.com.
- Data_science wikiPageExternalLink www.datacurry.in.
- Data_science wikiPageExternalLink datasciencesummit.
- Data_science wikiPageExternalLink index.htm.
- Data_science wikiPageExternalLink www.kaggle.com.
- Data_science wikiPageID "35458904".
- Data_science wikiPageRevisionID "606062165".
- Data_science hasPhotoCollection Data_science.
- Data_science subject Category:Computer_occupations.
- Data_science subject Category:Information_science.
- Data_science comment "Data science is the study of the generalizable extraction of knowledge from data, yet the key word is science.".
- Data_science label "Data science".
- Data_science label "Science des données".
- Data_science label "Наука о данных".
- Data_science label "データサイエンス".
- Data_science sameAs Science_des_données.
- Data_science sameAs データサイエンス.
- Data_science sameAs Data_scientist.
- Data_science sameAs m.0jt3_q3.
- Data_science sameAs Q2374463.
- Data_science sameAs Q2374463.
- Data_science wasDerivedFrom Data_science?oldid=606062165.
- Data_science depiction Data_Science_Venn_Diagram.png.
- Data_science isPrimaryTopicOf Data_science.
