Bookbot

Data Preparation for Analytics Using SAS

Évaluation du livre

En savoir plus sur le livre

Written for anyone involved in the data preparation process for analytics, Gerhard Svolba's Data Preparation for Analytics Using SAS offers practical advice in the form of SAS coding tips and tricks, and provides the reader with a conceptual background on data structures and considerations from a business point of view. The tasks addressed include viewing analytic data preparation in the context of its business environment, identifying the specifics of predictive modeling for data mart creation, understanding the concepts and considerations of data preparation for time series analysis, using various SAS procedures and SAS Enterprise Miner for scoring, creating meaningful derived variables for all data mart types, using powerful SAS macros to make changes among the various data mart structures, and more!

Achat du livre

Data Preparation for Analytics Using SAS, Gerhard Svolba

Langue
Année de publication
2006
product-detail.submit-box.info.binding
(souple)
Nous vous informerons par e-mail dès que nous l’aurons retrouvé.

Modes de paiement

5,0
Excellent
1 Évaluations

Il manque plus que ton avis ici.

Titre
Data Preparation for Analytics Using SAS
Langue
Anglais
Éditeur
SAS Press
Publié
2006
Format
souple
ISBN10
1599940477
ISBN13
9781599940472
Séries
Évaluation
5 sur 5
Description
Written for anyone involved in the data preparation process for analytics, Gerhard Svolba's Data Preparation for Analytics Using SAS offers practical advice in the form of SAS coding tips and tricks, and provides the reader with a conceptual background on data structures and considerations from a business point of view. The tasks addressed include viewing analytic data preparation in the context of its business environment, identifying the specifics of predictive modeling for data mart creation, understanding the concepts and considerations of data preparation for time series analysis, using various SAS procedures and SAS Enterprise Miner for scoring, creating meaningful derived variables for all data mart types, using powerful SAS macros to make changes among the various data mart structures, and more!