SCSUG 2008 Papers - Index

18 papers. Source: SCSUG (South-Central SAS Users Group) conference proceedings.

#	Title ×	Authors ×	Abstract ×	Keywords ×	Pages
1	A Propaedeutics for PROC SQL Joins	Lisa A. Mendez, Toby Dunn	Would you like to be able to join information from separate tables quickly and easily? Have you ever had two or more tables that you want to join but just don't know where to begin? If the answer is "yes" then "Join" us for a crash course over `PROC SQL` joins. This paper will help get you started by introducing you to the four basic types of SQL joins: inner, outer, natural, and Cartesian. Through the use of carefully crafted examples and detailed explanations we will take you on a guided tour of the SQL joins in SAS	inner join, where statement, proc sql, data merging, proc step, full join, normalization, cross join, right join	9
2	A Step by Step Procedure for Matching Addresses/Names in SAS	Pramod Sambidi, Himanshu Joshi
3	Estimating Price Elasticity of Demand for Consumer Credit in Automated Online Environment Using SAS	Liyan Zhao, Feng Xu
4	Find Out What You're Missing: Programming with SAS Enterprise Guide	Chris Hemedinger
5	Fun With SAS Formats	Bob Ramsey
6	Get Better Mileage (Efficiency) From Your SAS Programs	Keith Cranford
7	Integrating SAS and Geographic Information Systems for Regional Land Use Planning	Bill Bass
8	Iterative Proportional Fitting and Population Dynamics using SAS	Himanshu Joshi, Dmitry Messen
9	Measuring Campaign Performance by Using Cumulative Gain and Lift Chart	Tariq S. Jaffery, Shirley Liu
10	Optimizing Marketing Campaign ROI through Process Automation	Tariq S. Jaffery, Shirley Liu, Rick Vela	This paper provides solutions to campaign management challenges that perhaps every marketing company experiences while managing & reporting direct marketing campaigns. To optimize marketing campaign ROI, the campaign tracking teams need to respond quickly on targeted population behavior during a campaign and evaluate campaign effectiveness after a campaign has ended. The Customer Insight & Campaign Management is highly data intensive and a challenge particularly when you have to manage data from disparate sources. By using SAS we were able to improve the operating efficiencies through systems integration & automation of data intensive processes. Business rules were embedded within the SASapplication to further reduce the data processing time and ensure the integrity of the data. The application provides campaign behavior snapshot and significantly reduces time required to produce the final campaign reports. This allows time for understanding the data and developing campaign insight	data validation rules, data cleaning, macro variable	5
11	PROC REPORT - Your How-to Guide for Producing Customized Summary Tables	Deborah B. Buck	A numbe r of years ag o SAS developers res ponded to reques ts from SAS programmers f or a single report-writing procedu re that in corporated the features of `PROC PRINT`, `PROC` ME ANS, `PROC TABULATE`, and the DATA `_NULL_` step. The resulting procedure, `PROC REPORT`, is highly versatile with the capabilities to produce both detail and summary reports. In this workshop we will focus on `PROC REPORT` statements that will produce complex summary tables which include multiple dimensions, frequently reported descriptive statistics, columns of information not included in the data set, and customized summary statements. Although `PROC REPORT` can be used in a wi ndowing environment with p oint-and-click report building, we will use a programming approach to create the reports. This workshop is intended primarily for beginning to intermediate SAS users, or anyone who would like to become more familiar with `PROC REPORT`, and is applicable to all operating systems	proc report, proc step, dataset, missing value, proc tabulate, proc print, class variable	13
12	PROC SQL for DATA Step Die-Hards	Christianna S. Williams
13	Reading Multiple XML Files into One SAS Data Set	Mayumi Takada
14	SAS Stat Studio: A Programming Environment for High-End Data Analysts	Rick Wicklin
15	Tailoring the use of SAS Enterprise Miner	Sascha Schubert
16	Transaction Tracing	Liang Xie	This paper examines an innovative method to leverage information from a collection of sparse activities. By sparse, it means recorded activi- ties among monitored subjects are rare, and a typical example is recorded customers' behavior on tagged web page. A customer may browse certain web pages during a long time interval, and each tagged web page gets hits only from a small portion of marketing eligible customers. The final Customer-WebHits matrix will be a sparse matrix. Traditional statistical methods are not very effective in dealing with this kind of sparse data. Even though we can resort to techniques such as Principle Component Analysis (PCA) or variable clustering (VARCLUS) to reduce the number of variables, these unsupervised classification meth- `ODS` don't fully explore the relationship between all these variables and dependent variable, and more often than not their predictive power is not strong enough	dimensionality reduction, predictor variable, correlation, poisson distribution	7
17	Understanding WHERE Clause Processing and Indexes	Kirk Paul Lafler
18	Using SAS Business Intelligence Server and SAS Data Integration Studio with academic research data	Kevin Davidson

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