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Erstausgabe
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Broschiert. Zustand: Gut. 410 Seiten; Das hier angebotene Buch stammt aus einer teilaufgelösten wissenschaftlichen Bibliothek und trägt die entsprechenden Kennzeichnungen (Rückenschild, Instituts-Stempel.); Schnitt und Einband sind etwas staubschmutzig; der Buchzustand ist ansonsten ordentlich und dem Alter entsprechend gut. Text in ENGLISCHER Sprache! Sprache: Englisch Gewicht in Gramm: 860.
Zustand: New. Unlike the theoretical texts on statistics or data mining, this practical book should help database administrators improve their understanding of statistics and how to use SQL in their daily routines of data mining and data analysis. Each chapter can be read independently of the others and has numerous examples of business applications. Num Pages: 426 pages, 151 black & white illustrations, biography. BIC Classification: UMC; UMT; UNC; UNS. Category: (G) General (US: Trade). Dimension: 235 x 191 x 22. Weight in Grams: 816. . 2001. First Edition. paperback. . . . . Books ship from the US and Ireland.
Anbieter: Ria Christie Collections, Uxbridge, Vereinigtes Königreich
EUR 54,01
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In den WarenkorbZustand: New. In.
Taschenbuch. Zustand: Neu. Data Mining and Statistical Analysis Using SQL | John Lovett (u. a.) | Taschenbuch | xvi | Englisch | 2001 | Apress | EAN 9781893115545 | Verantwortliche Person für die EU: APress in Springer Science + Business Media, Heidelberger Platz 3, 14197 Berlin, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.
Zustand: Gut. Zustand: Gut | Seiten: 432 | Sprache: Englisch | Produktart: Bücher | This book is not just another theoretical text about statistics or data mining. No, instead it is aimed for database administrators who want to use SQL or bolster their understanding of statistics to support data mining and customer relationship management analytics. Each chapter is self-contained, with examples tailored to real business applications. And each analysis technique will be expressed in a mathematical format for coding as either a database query or a Visual Basic procedure using SQL. Chapter contents include formulas, graphs, charts, tables, data mining techniques, and more!