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Show Notes
Data Science and Big Data Analytics (EMC Education Services)
- Amazon USA Store: https://www.amazon.com/dp/111887613X?tag=9natree-20
- Amazon Worldwide Store: https://global.buys.trade/Data-Science-and-Big-Data-Analytics-EMC-Education-Services.html
- Apple Books: https://books.apple.com/us/audiobook/data-science-and-big-data-data-science-and-big/id1752109409?itsct=books_box_link&itscg=30200&ls=1&at=1001l3bAw&ct=9natree
- eBay: https://www.ebay.com/sch/i.html?_nkw=Data+Science+and+Big+Data+Analytics+EMC+Education+Services+&mkcid=1&mkrid=711-53200-19255-0&siteid=0&campid=5339060787&customid=9natree&toolid=10001&mkevt=1
- Read more: https://english.9natree.com/read/111887613X/
#Dataanalyticslifecycle #Structuredandunstructureddataintegration #Classificationregressionandclustering #Timeseriesandtextanalysis #Datavisualizationandpresentation #DataScienceandBigDataAnalytics
Data Science and Big Data Analytics: Discovering, Analyzing, Visualizing and Presenting Data is a practitioner-focused instructional book developed by EMC Education Services and published by Wiley in 2015. It surveys the work of a data science team, from framing an analytics problem and preparing data through model building, visualization, and communication of results. Rather than treating big data as only a storage or infrastructure issue, the book connects diverse and high-volume data sources to analytical decision making. Its twelve-chapter structure introduces the data analytics lifecycle alongside core methods such as classification, regression, clustering, time series analysis, and text analysis. Examples and open-source tools support the applied orientation, while exercises and chapter summaries reinforce the curriculum format. The book was also designed to support preparation for the EMC Data Science Associate certification. Its central purpose is to give analysts, technical professionals, managers, and prospective data scientists a shared framework for participating effectively in analytics projects and translating data-driven findings into business-relevant action.
- Amazon USA Store: https://www.amazon.com/dp/111887613X?tag=9natree-20
- Amazon Worldwide Store: https://global.buys.trade/Data-Science-and-Big-Data-Analytics-EMC-Education-Services.html
- Apple Books: https://books.apple.com/us/audiobook/data-science-and-big-data-data-science-and-big/id1752109409?itsct=books_box_link&itscg=30200&ls=1&at=1001l3bAw&ct=9natree
- eBay: https://www.ebay.com/sch/i.html?_nkw=Data+Science+and+Big+Data+Analytics+EMC+Education+Services+&mkcid=1&mkrid=711-53200-19255-0&siteid=0&campid=5339060787&customid=9natree&toolid=10001&mkevt=1
- Read more: https://english.9natree.com/read/111887613X/
#Dataanalyticslifecycle #Structuredandunstructureddataintegration #Classificationregressionandclustering #Timeseriesandtextanalysis #Datavisualizationandpresentation #DataScienceandBigDataAnalytics
Data Science and Big Data Analytics: Discovering, Analyzing, Visualizing and Presenting Data is a practitioner-focused instructional book developed by EMC Education Services and published by Wiley in 2015. It surveys the work of a data science team, from framing an analytics problem and preparing data through model building, visualization, and communication of results. Rather than treating big data as only a storage or infrastructure issue, the book connects diverse and high-volume data sources to analytical decision making. Its twelve-chapter structure introduces the data analytics lifecycle alongside core methods such as classification, regression, clustering, time series analysis, and text analysis. Examples and open-source tools support the applied orientation, while exercises and chapter summaries reinforce the curriculum format. The book was also designed to support preparation for the EMC Data Science Associate certification. Its central purpose is to give analysts, technical professionals, managers, and prospective data scientists a shared framework for participating effectively in analytics projects and translating data-driven findings into business-relevant action.
