Large scale data analytics (167 résultats)

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Etat : Good. Item in good condition. Textbooks may not include supplemental items i.e. CDs, access codes etc.

Paperback. Etat : Good. Good paperback. Text has a few markings. Covers show minor wear.; 100% Satisfaction Guaranteed! Ships same or next business day.

Etat : Very Good. 1st Edition. Former library copy. Pages intact with possible writing/highlighting. Binding strong with minor wear. Dust jackets/supplements may not be included. Includes library markings. Stock photo provided. Product includes identifying sticker. Better World Books: Buy Books. Do Good.…

Etat : Very Good. 1st Edition. Former library copy. Pages intact with possible writing/highlighting. Binding strong with minor wear. Dust jackets/supplements may not be included. Includes library markings. Stock photo provided. Product includes identifying sticker. Better World Books: Buy Books. Do Good.…

Paperback. Etat : Very Good. Making Big Data Work: Real-World Use Cases and Examples, Practical Code, Detailed Solutions   Large-scale data analysis is now vitally important to virtually every business. Mobile and social technologies are generating massive datasets; distributed cloud computing offers the resources to store and analyze them; and professionals have radically new technologies at their command, including NoSQL databases. Until now, however, most books on ?Big Data? have been little more than business polemics or product catalogs. Data Just Right is different: It?s a completely practical and indispensable guide for every Big Data decision-maker, implementer, and strategist.   Michael Manoochehri, a former Google engineer and data hacker, writes for professionals who need practical solutions that can be implemented with limited resources and time. Drawing on his extensive experience, he helps you focus on building applications, rather than infrastructure, because that?s where you can derive the most value.   Manoochehri shows how to address each of today?s key Big Data use cases in a cost-effective way by combining technologies in hybrid solutions. You?ll find expert approaches to managing massive datasets, visualizing data, building data pipelines and dashboards, choosing tools for statistical analysis, and more. Throughout, the author demonstrates techniques using many of today?s leading data analysis tools, including Hadoop, Hive, Shark, R, Apache Pig, Mahout, and Google BigQuery.   Coverage includes Mastering the four guiding principles of Big Data success?and avoiding common pitfalls Emphasizing collaboration and avoiding problems with siloed data Hosting and sharing multi-terabyte datasets efficiently and economically ?Building for infinity? to support rapid growth Developing a NoSQL Web app with Redis to collect crowd-sourced data Running distributed queries over massive datasets with Hadoop, Hive, and Shark Building a data dashboard with Google BigQuery Exploring large datasets with advanced visualization Implementing efficient pipelines for transforming immense amounts of data Automating complex processing with Apache Pig and the Cascading Java library Applying machine learning to classify, recommend, and predict incoming information Using R to perform statistical analysis on massive datasets Building highly efficient analytics workflows with Python and Pandas Establishing sensible purchasing strategies: when to build, buy, or outsource Previewing emerging trends and convergences in scalable data technologies and the evolving role of the Data Scientist.…

Paperback. Etat : Good. Making Big Data Work: Real-World Use Cases and Examples, Practical Code, Detailed Solutions   Large-scale data analysis is now vitally important to virtually every business. Mobile and social technologies are generating massive datasets; distributed cloud computing offers the resources to store and analyze them; and professionals have radically new technologies at their command, including NoSQL databases. Until now, however, most books on ?Big Data? have been little more than business polemics or product catalogs. Data Just Right is different: It?s a completely practical and indispensable guide for every Big Data decision-maker, implementer, and strategist.   Michael Manoochehri, a former Google engineer and data hacker, writes for professionals who need practical solutions that can be implemented with limited resources and time. Drawing on his extensive experience, he helps you focus on building applications, rather than infrastructure, because that?s where you can derive the most value.   Manoochehri shows how to address each of today?s key Big Data use cases in a cost-effective way by combining technologies in hybrid solutions. You?ll find expert approaches to managing massive datasets, visualizing data, building data pipelines and dashboards, choosing tools for statistical analysis, and more. Throughout, the author demonstrates techniques using many of today?s leading data analysis tools, including Hadoop, Hive, Shark, R, Apache Pig, Mahout, and Google BigQuery.   Coverage includes Mastering the four guiding principles of Big Data success?and avoiding common pitfalls Emphasizing collaboration and avoiding problems with siloed data Hosting and sharing multi-terabyte datasets efficiently and economically ?Building for infinity? to support rapid growth Developing a NoSQL Web app with Redis to collect crowd-sourced data Running distributed queries over massive datasets with Hadoop, Hive, and Shark Building a data dashboard with Google BigQuery Exploring large datasets with advanced visualization Implementing efficient pipelines for transforming immense amounts of data Automating complex processing with Apache Pig and the Cascading Java library Applying machine learning to classify, recommend, and predict incoming information Using R to perform statistical analysis on massive datasets Building highly efficient analytics workflows with Python and Pandas Establishing sensible purchasing strategies: when to build, buy, or outsource Previewing emerging trends and convergences in scalable data technologies and the evolving role of the Data Scientist.…

Paperback. Etat : Fair. 1st ed. The item might be beaten up but readable. May contain markings or highlighting, as well as stains, bent corners, or any other major defect, but the text is not obscured in any way.

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Paperback. Etat : Good. No Jacket. Pages can have notes/highlighting. Spine may show signs of wear. ~ ThriftBooks: Read More, Spend Less.

Paperback. Etat : Good. No Jacket. Pages can have notes/highlighting. Spine may show signs of wear. ~ ThriftBooks: Read More, Spend Less.

Etat : Good. Your purchase helps support Sri Lankan Children's Charity 'The Rainbow Centre'. Ex-library, so some stamps and wear, but in good overall condition. Our donations to The Rainbow Centre have helped provide an education and a safe haven to hundreds of children who live in appalling conditions.…

paperback. Etat : Very Good. Minor shelf wear on cover.

paperback. Etat : Good. Cover/edges are worn and or have small tears, otherwise good reading copy.

Etat : very good. Gently used. May include previous owner's signature or bookplate on the front endpaper, sticker on back and/or remainder mark on text block.

paperback. Etat : VeryGood. A copy that may have been read, very minimal wear and tear. May have a remainder mark.

Etat : New.

Etat : New. In English.

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paperback. Etat : New. 1st Edition. Ships in a BOX from Central Missouri! UPS shipping for most packages, (Priority Mail for AK/HI/APO/PO Boxes).

paperback. Etat : New. In stock.

Paperback. Etat : Very Good.

Etat : New.

Etat : New.

Etat : New.

Etat : New. Brand New! Not Overstocks or Low Quality Book Club Editions! Direct From the Publisher! We're not a giant, faceless warehouse organization! We're a small town bookstore that loves books and loves it's customers! Buy from Lakeside Books.

Etat : As New. Unread book in perfect condition.

Etat : New.