Tools

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010 a| 2007275525;

020 a| 9781599940472;

020 a| 1599940477;

035 a| (WaSeSS)ssj0000074379;

040 a| SA$c| SA$d| SA$d| BAKERd| DLCd| WaSeSS;

042 a| lccopycat;

049 a| EREEa| NEHH;

050 00 a| HF5548.2b| .S875 2006;

100 1 a| Svolba, Gerhard.=| ^A886408;

245 10 a| Data preparation for analytics using SASh| [electronic resource] /c| Gerhard Svolba.;

260 a| Cary, NC :b| SAS Institute,;

300 a| xxii, 408 p. :b| ill. ;c| 28 cm.;

440 0 a| SAS Press series;

500 a| Includes index.;

505 0 a| Pt. 1. Data preparation: business point of view -- ch. 1. Analytic business questions -- Ch. 2. Characteristics of analytic business questions -- Ch. 3. Characteristics of data sources -- Ch. 4. Different points of view on analytic data preparation -- Pt. 2. Data structures and data modeling -- Ch. 5. The origin of data -- Ch. 6. Data models -- Ch. 7. Analysis subjects and multiple observations -- Ch. 8. The one row-per-subject data mart -- Ch. 9. The multiple-rows-per-subject data mart -- Ch. 10. Data structures for longitudinal analysis -- Ch. 11. Considerations for data marts -- Ch. 11. Considerations for predictive modeling -- Pt. 3. Data mart coding and content -- Ch. 13. Accessing data -- Ch. 14. Transposing one- and multiple-rows-per-subject data structures -- Ch. 15. Transposing longitudinal data -- Ch. 16. Transformations of interval-scaled variables -- Ch. 17. Transformations of categorical variables -- Ch. 18. Multiple interval-scaled observations per subject -- Ch. 19. Multiple catagorical observations per subject -- Ch. 20. Coding for predictive modeling -- Ch. 21. Data preparation for multiple-rows-per-subject and longitudinal data marts -- Pt. 4. Sampling, scoring, and automation -- Ch. 22. Sampling -- Ch. 23. Scoring and automation -- Ch 24. Do's and don'ts when building data marts -- Pt. 5. Case studies.;

506 a| Available only to authorized users.;

538 a| Mode of access: World Wide Web;

630 00 a| SAS (Computer file)=| ^A297874;

630 00 a| Enterprise Miner.=| ^A886410;

650 0 a| Businessx| Data processing.=| ^A15966;

650 0 a| Electronic data processing.=| ^A427280;

650 0 a| Commercial analysis.?| UNAUTHORIZED;

650 0 a| Data marts.=| ^A813088;

650 0 a| Data mining.=| ^A408868;

650 0 a| Time-series analysis.=| ^A7961;

655 0 a| Electronic books.=| ^A491897;

710 2 a| SAS Institute.=| ^A85352;

856 40 z| Full text available from eBooks on EBSCOhostu| https://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&AN=180232&scope=site&custid=s5822723&authtype=ip,shib;

947 a| (OCoLC)ocm82171634;

949 a| CLICK ON WEB ADDRESSw| ASISh| JOYNER188;

949 a| CLICK ON WEB ADDRESSw| ASISh| HSL77;

949 a| CLICK ON WEB ADDRESSw| ASISh| JMUSIC60;

596 a| 1 3 4;

998 a| 5680200;

999 a| CLICK ON WEB ADDRESSw| ASISc| 1i| 5680200-1001l| JNETm| JOYNERr| Ys| Yt| JNESSBKu| 9/17/2021x| EBOOKz| JERESOURCE;

999 a| CLICK ON WEB ADDRESSw| ASISc| 1i| 5680200-2001l| HSLELECm| HSLr| Ys| Yt| HEBKu| 9/17/2021x| EBOOKz| HERESOURCE;

999 a| CLICK ON WEB ADDRESSw| ASISc| 1i| 5680200-3001l| MNETm| JMUSICr| Ys| Yt| MNESSBKu| 9/17/2021x| EBOOKz| JERESOURCE;

Data preparation for analytics using SAS / Gerhard Svolba.

Author/creator	Svolba, Gerhard
Other author	SAS Institute.
Format	Electronic
Publication Info	Cary, NC : SAS Institute,
Description	xxii, 408 p. : ill. ; 28 cm.
Supplemental Content	Full text available from eBooks on EBSCOhost
Subjects	SAS (Computer file) Enterprise Miner. Business--Data processing. Electronic data processing. Commercial analysis. Data marts. Data mining. Time-series analysis.

Series	SAS Press series
Contents	Pt. 1. Data preparation: business point of view -- ch. 1. Analytic business questions -- Ch. 2. Characteristics of analytic business questions -- Ch. 3. Characteristics of data sources -- Ch. 4. Different points of view on analytic data preparation -- Pt. 2. Data structures and data modeling -- Ch. 5. The origin of data -- Ch. 6. Data models -- Ch. 7. Analysis subjects and multiple observations -- Ch. 8. The one row-per-subject data mart -- Ch. 9. The multiple-rows-per-subject data mart -- Ch. 10. Data structures for longitudinal analysis -- Ch. 11. Considerations for data marts -- Ch. 11. Considerations for predictive modeling -- Pt. 3. Data mart coding and content -- Ch. 13. Accessing data -- Ch. 14. Transposing one- and multiple-rows-per-subject data structures -- Ch. 15. Transposing longitudinal data -- Ch. 16. Transformations of interval-scaled variables -- Ch. 17. Transformations of categorical variables -- Ch. 18. Multiple interval-scaled observations per subject -- Ch. 19. Multiple catagorical observations per subject -- Ch. 20. Coding for predictive modeling -- Ch. 21. Data preparation for multiple-rows-per-subject and longitudinal data marts -- Pt. 4. Sampling, scoring, and automation -- Ch. 22. Sampling -- Ch. 23. Scoring and automation -- Ch 24. Do's and don'ts when building data marts -- Pt. 5. Case studies.
General note	Includes index.
Access restriction	Available only to authorized users.
Technical details	Mode of access: World Wide Web
Genre/form	Electronic books.
LCCN	2007275525
ISBN	9781599940472
ISBN	1599940477

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