isqs 6347, data & text mining 1 isqs 6339, data management & business intelligence data...

ISQS 6347, Data & Text Mining 1

ISQS 6339, Data Management & Business Intelligence

Data Preparation for Analytics Using SAS

Zhangxi Lin

Texas Tech University


Outline

An overview of data preparation for analytics SAS Programming Essentials

Running SAS programs Mastering fundamental concepts SAS program debugging

Make use of SAS Enterprise Guide for programming


Structure and Components of Business Intelligence


Overview: From Data Warehousing to Data Analysis Previous major topics in data warehousing (using SQL Server

2008) Dimensional model design ETL Cubes design and OLAP

Data analysis topics (using SAS) Data preparation

Analytic business questions Data format and data conversion

Data cleansing Data exploratory Data analysis Data visualization


US Car Theft

The number of U.S. motor vehicle thefts decreased by 1.9 percent from 2003 to 2004, the first decrease since 1999. In 2004, the value of stolen motor vehicles was $7.6 billion, down from $8.6 billion in 2003. The average value of a motor vehicle reported stolen in 2004 was $6,143, compared with $6,797 in 2003.


2004 Theft Statistics

Every 26 seconds, a motor vehicle is stolen in the United States. The odds of a vehicle being stolen were 1 in 190 in 2003. The odds are highest in urban areas.

U.S. motor vehicle thefts fell 1.9 percent in 2004 from 2003, according to the FBI's Uniform Crime Reports. In 2004, 1,237,114 motor vehicles were reported stolen.

The West was the only region with an increase in motor vehicle thefts from 2003 to 2004, up 3.2 percent. Thefts fell 9.7 percent in the Northeast, 4.4 percent in the Midwest and 2.9 percent in the South.

Nationwide, the 2004 motor vehicle theft rate per 100,000 people was 421.3, down 2.9 percent from 433.7 in 2003.

Only 13.0 percent of thefts were cleared by arrests in 2004. Carjackings occur most frequently in urban areas. They account

for only 3.0 percent of all motor vehicle thefts. The average comprehensive insurance premium in the U.S. rose

11.2 percent from 1999 to 2003


Business Question

If the number of used Honda Accord thefts is ranked the top in auto theft, should the premium of insurance for Honda Accord be high enough than other brand of cars? Should the insurance for a user Honda higher than a brand new Honda?

Why?


Analytic Business Questions

How do factors such as time, branch, promotion, and price influence the sale of a soft drink?

Which customers have a high cancellation risk in the next month? How can customers be segmented based on their purchase

behavior? Statistics showed that an online recommendation system may

increase the sale 20%, and the accuracy rate of the system is 40%. A newer algorithm can increase the accuracy rate to 50%. Should the sale be promoted to 20%*125% = 25%?

The airline companies are considering allowing seats over-booked because certain percentage of customers will cancel their flight at the last minute. If the average cancellation rate is 10%, should the over-booking rate be 10% as well? If a cancellation is charged 5% of the fare and how much should the penalty for sold-out situation with over-booking?


Analysis Process

Selecting an analysis method Identify data source Prepare the data (collecting, cleansing, reorganizing, extracting

transforming, loading) Execute the analysis Interpret the analysis Automate data preparation and execution of analysis, if the

business question has to be answered more than once ETL Stored procedures

The above steps can also be iterated, not necessarily performed in sequential order

We focus on the data preparation step


Characteristics of Analytic Business Questions Analysis complexity: real analysis or reporting Analysis paradigm: statistics or data mining Data preparation paradigm: as much as data as possible or

business knowledge first Analysis method: supervised or unsupervised analysis Scoring needed – yes/no Periodicity of analysis: one-shot or re-run Historic data needed, yes/no Data structure: one row or multiple rows per subject Complexity of the analysis team


Components of the SAS System

ReportingAnd

Graphics

Data AccessAnd

Management

UserInterface

Analytical Base SASApplication

Development

VisualizationAnd Discovery

BusinessSolutions

WebEnablement


SAS Programming Essentials

Find more information from http://support.sas.com


Data-driven Tasks

The functionality of the SAS System is built around four data-driven tasks common to virtually any applications Data access Data management Data analysis Data presentation


Turning Data into Information Process of delivery meaningful information

80% data-related Access Scrub Transform Mange Store and retrieve

20% analysis


DATAStep

SAS Data Sets

Data

PROCSteps

Information

Turning Data into Information


PCPC WorkstationWorkstationServers//Midrange MainframeMainframe

SuperComputer

90%independent

10%dependent

MultiVendor Architecture

Design of the SAS System

...


MultiEngine Architecture

Design of the SAS System

DATADATA

Teradata

SYBASE

Microsoft ExcelORACLE

dBase

SAP

DB2


SAS Programming – Level I Fundamentals (ch1-3) Producing list reports (ch4) Enhancing output (ch5) Creating data sets (ch6) Data step programming (ch7)

Reading data Creating variables Conditional processing Keeping and dropping variables Reading Excel files

Combining SAS data sets (ch8) Producing summary reports (ch9) SAS graphing (ch10)


In this course, you work with business data from International Airlines (IA). The various kinds of data that IA maintains are listed below: flight data passenger data cargo data employee data revenue data

Course Scenario


The following are some tasks that you will perform: importing data creating a list of employees producing a frequency table of job codes summarizing data creating a report of salary information

Course Scenario


DATA steps are typically used to create SAS data sets.

PROC steps are typically used to process SAS data sets (that is, generate reports and graphs, edit data, and sort data).

A SAS program is a sequence of steps that the user submits for execution.

RawData

RawData

DATAStep

DATAStep

ReportReport

SASDataSet

SASDataSet

PROCStep

PROCStep

SAS Programs


data work.staff; infile 'raw-data-file'; input LastName $ 1-20 FirstName $ 21-30 JobTitle $ 36-43 Salary 54-59;run;

proc print data=work.staff;run;

proc means data=work.staff; class JobTitle; var Salary;run;

DATAStep

PROCSteps

SAS Programs


SAS steps begin with either of the following: DATA statement PROC statement

SAS detects the end of a step when it encounters one of the following: a RUN statement (for most steps) a QUIT statement (for some procedures) the beginning of another step (DATA statement

or PROC statement)

Step Boundaries



proc print data=work.staff;


Step Boundaries


You can invoke SAS in the following ways: interactive windowing mode (SAS windowing

environment) interactive menu-driven mode (SAS Enterprise Guide,

SAS/ASSIST, SAS/AF, or SAS/EIS software) batch mode noninteractive mode

Running a SAS Program


Preparation of SAS Programming Data sets: \SAS-Programming Create a user defined library reference

Statement

LIBNAME libref ‘SAS-data-library’ <options>;

Example

LIBNAME ia ‘c:\workshop\winsas\prog1’;

Two-levels of SAS files namesLibref.fielname


SAS Programming Essentials

Demon: c02s2d1 Exercise: c02ex1


General form of the CONTENTS procedure:

Example:

PROC CONTENTS DATA=SAS-data-set;RUN;

PROC CONTENTS DATA=SAS-data-set;RUN;

proc contents data=work.staff;run;

Browsing the Descriptor Portion

c02s3d1


Numeric values

Variable

names

Variable

values

LastName FirstName JobTitle Salary

TORRES JAN Pilot 50000LANGKAMM SARAH Mechanic 80000SMITH MICHAEL Mechanic 40000WAGSCHAL NADJA Pilot 77500TOERMOEN JOCHEN Pilot 65000

The data portion of a SAS data set is a rectangular table of character and/or numeric data values.

Variable names are part of the descriptor portion, not the data portion.

Character values

SAS Data Sets: Data Portion


SAS Variable Values

There are two types of variables:

character contain any value: letters, numbers, special characters, and blanks. Character values are stored with a length of 1 to 32,767 bytes. One byte equals one character.

numeric stored as floating point numbers in 8 bytes of storage by default. Eight bytes of floating point storage provide space for 16 or 17 significant digits. You are not restricted to 8 digits.


SAS names have these characteristics: can be 32 characters long. can be uppercase, lowercase, or mixed-case. are not case sensitive. must start with a letter or underscore.

Subsequent characters can be letters, underscores, or numerals.

SAS Data Set and Variable Names


data5mon

Select the valid default SAS names.

Valid SAS Names

...



Valid SAS Names

...

data5mon


data5mon


data5mon

5monthsdata

Valid SAS Names

...


data5mon


data5mon

5monthsdata

Valid SAS Names

...

data#5


data5mon


data5mon

5monthsdata

Valid SAS Names

...

data#5

five months data


data5mon


data5mon

5monthsdata

five months data

data#5

Valid SAS Names

...

fivemonthsdata


data5mon


data5mon

5monthsdata

five months data

data#5

Valid SAS Names

...

fivemonthsdata

FiveMonthsData


LastName FirstName JobTitle Salary

TORRES JAN Pilot 50000LANGKAMM SARAH Mechanic 80000SMITH MICHAEL Mechanic . WAGSCHAL NADJA Pilot 77500TOERMOEN JOCHEN 65000

A value must exist for every variable for each observation.

Missing values are valid values.

A numeric missing value is displayed as a period.

A character missing value is displayed as a blank.

Missing Data Values


The PRINT procedure displays the data portion of a SAS data set.

By default, PROC PRINT displays the following: all observations all variables an Obs column on the left side

Browsing the Data Portion


General form of the PRINT procedure:

Example:

PROC PRINT DATA=SAS-data-set;RUN;

PROC PRINT DATA=SAS-data-set;RUN;


Browsing the Data Portion

c02s3d1


SAS documentation and text in the SAS windowing environment use the following terms interchangeably:

SAS Data SetSAS Data Set SAS TableSAS Table

VariableVariable ColumnColumn

ObservationObservation RowRow

SAS Data Set Terminology


SAS statements have these characteristics: usually begin with an identifying keyword always end with a semicolon




SAS Syntax Rules


SAS statements are free-format. One or more blanks or special characters can

be used to separate words. They can begin and end in any column. A single statement can span multiple lines. Several statements can be on the same line.

Unconventional Spacing

data work.staff; infile 'raw-data-file';input LastName $ 1-20 FirstName $ 21-30JobTitle $ 36-43 Salary 54-59;run; proc means data=work.staff; class JobTitle; var Salary;run;

SAS Syntax Rules

...






SAS Syntax Rules

...



...




SAS Syntax Rules

...



...




SAS Syntax Rules


Good spacing makes the program easier to read.

Conventional Spacing




SAS Syntax Rules


Type /* to begin a comment. Type your comment text. Type */ to end the comment.

/* Create work.staff data set */data work.staff; infile 'raw-data-file'; input LastName $ 1-20 FirstName $ 21-30 JobTitle $ 36-43 Salary 54-59;run;

/* Produce listing report of work.staff */proc print data=work.staff;run;

SAS Comments

c02s3d2


daat work.staff; infile 'raw-data-file'; input LastName $ 1-20 FirstName $ 21-30 JobTitle $ 36-43 Salary 54-59;run;

proc print data=work.staff run;

proc means data=work.staff average max; class JobTitle; var Salary;run;

Syntax errors include the following: misspelled keywords missing or invalid punctuation invalid options

Syntax Errors


This demonstration illustrates how to submit a SAS program that contains errors, diagnose the errors, correct the errors, and save the corrected program.

Debugging a SAS Program c02s4d1.sas userid.prog1.sascode(c02s4d1) c02s4d2.sas userid.prog1.sascode(c02s4d2)


daat work.staff; infile 'raw-data-file'; input LastName $ 1-20 FirstName $ 21-30 JobTitle $ 36-43 Salary 54-59;run;proc print data=work.staff run;proc means data=work.staff average max; class JobTitle; var Salary;run;data work.staff; infile 'raw-data-file'; input LastName $ 1-20 FirstName $ 21-30 JobTitle $ 36-43 Salary 54-59;run;proc print data=work.staff; run;proc means data=work.staff mean max; class Jobtitle; var Salary;run;

Program statements accumulate in a recall buffer each time you issue a SUBMIT command.

SubmitNumber 1

SubmitNumber 2

Recall a Submitted Program


SubmitNumber 1

SubmitNumber 2

Issue RECALLonce.

Submit Number 2 statementsare recalled.

Issue the RECALL command once to recall the most recently submitted program.

data work.staff; infile 'raw-data-file'; input LastName $ 1-20 FirstName $ 21-30 JobTitle $ 36-43 Salary 54-59;run;proc print data=work.staff; run;proc means data=work.staff mean max; class JobTitle; var Salary;run;



daat work.staff; infile 'raw-data-file'; input LastName $ 1-20 FirstName $ 21-30 JobTitle $ 36-43 Salary 54-59;run;proc print data=work.staff run;proc means data=work.staff average max; class JobTitle; var Salary;run;data work.staff; infile 'raw-data-file'; input LastName $ 1-20 FirstName $ 21-30 JobTitle $ 36-43 Salary 54-59;run;proc print data=work.staff; run;proc means data=work.staff mean max; class JobTitle; var Salary;run;

Issue the RECALL command again to recall Submit Number 1 statements.


SubmitNumber 1

SubmitNumber 2

Issue RECALLagain.


Exercise 8: Basic SAS Programming Define library IA and Out Go through all SAS programs in Chapter 2-5. Write a SAS program to read a dataset created by

yourself or simply use Person0.txt in \\TechShare\coba\d\ISQS3358\OtherDatasets\ .

The dataset is output to your library Out. Try to apply whatever SAS features in Chapter 5

of Prog-I to general a nice looking report.

Go through all exercises for Ch 2, 3, 4, 5, 6 (answer keys are available, so no need to submit the results)

Hands-on exercise

Write a SAS program to calculate the number of dates passed in 2012 to 3/3/2012. The input is in the format: date9.

01JAN2012 03MAR2012 Answer: 62 days



Making Use of SAS Enterprise Guide Code Import a text file

Example: Orders.txt Import an Excel file

Example: SupplyInfo.xls


Learn from Examples

SAS Help Contents -> Learning to use SAS -> Sample SAS

Programs -> Base SAS “Base Usage Guide Examples”

Chapter 3, 4


Import an Excel Sheet

proc import out=work.commrexdatafile ="C:\Lin\Shared\ISQS6339\Commrex_3358.xls" dbms=excel replace;

sheet="Company";getnames=yes;mixed=no;scantext=yes;usedate=yes;scantime=yes;run;proc print data=work.commrex;run;


Excel SAS/ACCESS LIBNAME Enginelibname xlsdata 'C:\Lin\Shared\ISQS6339\Commrex_3358.xls';

proc print data=xlsdata.New1;

run;


Exercise 9: SAS Data Step Programming http://zlin.ba.ttu.edu/6339/ExerciseInstructions9.htm

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