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SAS (BASE, ADVANCED)
SAS is the leader in analytics. Through innovative analytics, business intelligence and data management software and services, SAS helps customers at more than 80,000 sites make better decisions faster. Since 1976, SAS has been giving customers around the world
SAS, (pronounced “sass”) once stood for “Statistical Analysis System,”
But now it is only SAS.
SAS began at North Carolina State University as a project to analyze agricultural research. Founded in 1976 to help all sort of customers.
SAS is both software and company.
The world biggest private sector company.
SAS giving operations in various sectors like,
Automotive
Communications
Education
Banking/Financial Services
Government
Health Insurance
Health Care Providers
Hospitality & Entertainment
Insurance
Life Sciences
Manufacturing
Media
Oil & Gas
Retail
Hotels
Utilities
And giving solution lines as
Analytics
Business Intelligence
Customer Intelligence
Data Integration & ETL
Financial Intelligence
Foundation Tools
Fraud Management
Governance, Risk & Compliance
High-Performance Computing
Human Capital Intelligence
IT Management
On Demand Solutions
Performance Management
Risk Management
Supply Chain Intelligence
Sustainability Management
In 1966, there was no SAS.
But there was a need for a computerized statistics program to analyze vast amounts of agricultural data collected through
United States Department of Agriculture (USDA) grants.
Then research started by University Statisticians Southern Experiment Stations, Eight land-grant universities that received the majority of their research funding from the USDA. And some schools came together under a grant from the National Institutes of Health (NIH) to develop a general-purpose statistical software package to analyze all the agricultural data they were generating.
North Carolina State University, located in the capital city of Raleigh, North Carolina became the leader in the consortium.
North Carolina State University faculty members
Jim Goodnight and Jim Barr
Emerged as the project leaders –
Barr creating the architecture and
Goodnight implementing the features
In 1972 NIH stopped to give funds to this team, then the consortium agreed to chip in $5,000 apiece each year to allow NCSU to continue developing and maintaining the system and supporting their statistical analysis needs.
During the coming years, SAS software was licensed by pharmaceutical companies, insurance companies and banks, as well as by the academic community that had given birth to the project.
Jane Helwig, another Statistics Department employee at NCSU, Joined the project consortium as documentation writer
John Sall, a graduate student and programmer, rounded out the core team.
Incorporation
In 1976 Goodnight, Barr, Helwig and Sall left NCSU and formed
SAS Institute Inc. – a private company “devoted to the maintenance and further development of SAS.” They opened offices in a building #2806 Hillsborough Street, across from the university.
By 1980, the growing company building capacity is not sufficient in Hillsborough Street building, and then it’s moved to the site of its present headquarters offices just outside Raleigh in Cary, North Carolina. In that time employs were 20.
In this time SAS was growing, the entire computer hardware and software industry was changing, with new operating systems and platforms placing new demands on software developers one of the first steps for SAS was to adapt the software to operate on IBM’s Disk Operating System (DOS).
Now it is working on different operating systems like windows, Dos, Z/OS, UNIX and various UNIX flavors.
In 1990 SAS Company grow with employ force of 7000.
SAS celebrated its 25th anniversary in 2001,
Its turn out from various difficulties along with the millennium and the Y2K frenzy. And they created new logo and tagline presently which we are seeing Tagline is –
THE POWER TO KNOW®
SAS has been named one of FORTUNE magazine’s “100 Best Companies to Work For” every year since 1998 and no1 in 2010
SAS named the best company to work for in 2010 by FORTUNE.
SRINIVAS
FACULTY NAME: SRINIVAS
EDUCATION:MS
EXPERIANCE: 8+ YEARS OF WORK AND TEACHING IN SAS
SAS CERTIFIED CANDIDATE: BASE, ADVANCE AND CLINICAL SAS
SAS (BASE, ADVANCED)
SAS Base & Advance Course Content – Around 200 HOURS WHAT IS SAS and BASICS of SAS- 12HOURS BEGIN WITH DATASTEP - 10 HOURS ATTRIBUTES OF VARIABLES - 8 HOURS OTHER SAS STATEMENTS - 5 HOURS CONDITIONAL STATEMENTS - 4 HOURS LOOPS - 5 HOURS ARRAY – 5 HOURS BY - GROUP PROCESSING – 4 HOURS COMBINING SAS DATA SETS - 10 HOURS FUNCTIONS (100 + Functions) - 10 HOURS REVIEW OF DATASTEP - 2 HOURS SAS - PROCEDURES (PROC STEP) – 1 HOUR DATA ACCESS PROCEDURES - 4 HOURS UTILITY PROCEDURES - 15 HOURS STATISTICS &STATISTICAL PROCEDURES - 15 HOURS REPORTING PROCEDURES - 10 HOURS GRAPHICAL PROCEDURES - 5 HOURS REVIEW OF PROCSTEP - 2 HOURS ODS (OUTPUT DELIVERY SYSTM) - 5 HOURS SAS DDE (Dynamic Data Exchange) – 2 Hours DICTIONARY TABLES - 2 HOURS LIST OF GLOBAL STATEMENTS - 3 HOURS LIST OF GLOBAL OPTIONS - 5 HOURS PROC SQL – 20 HOURS INTRODUCTION TO THE SQL PROCEDURE RETRIEVING DATA FROM A SINGLE TABLE RETRIEVING DATA FROM MULTIPLE TABLES CREATING AND UPDATING TABLES AND VIEWS PROGRAMMING WITH THE SQL PROCEDURE PRACTICAL PROBLEM-SOLVING WITH PROC SQL SAS/MACROS - 20 HOURS PERFORMANCE TUNING CONCEPTS - 2 HOURS TESTING & DEBUGGING TECHNIQUES - 2 HOURS ERROR HANDLING - 2 HOURS FEATURES BETWEEN SAS VERSIONS V9 - 2 HOURS SAS WITH UNIX/LINUX ENVIRONMENT - 10 HOURS CERTIFICATION CLASSES - 10 HOURS SAS EG (Enterprise Guide) - 10 HOURS PROJECTS FREE CLASSES Along with SAS U will get Free classes which helps to make you more Understanding to get good & quick job. ELIGIBILITY: Clinical / Life science /Healthcare Domain Banking/Finance/Healthcare/Retail & Telecom Domain (Any graduate/ post graduate is eligible) For any queries please contact STANSYS Between Apollo Clinic & Nagarjuna High School, Sanjeevareddy Nagar, Hyderabad- 500038, Telangana.
Missing Data
Q #1) Enlist the functions performed by SAS.
Answer: SAS (Statistical Analysis System) has its own importance in every business domain.
Enlisted below are some of the summarized functions that are performed by SAS:
- Data Management and Project Management
- Data Warehousing
- Operational Research and decisional support
- Information Retrieval and Quality Management
- Business Planning
- Statistical Analysis
Q #2) What are the 3 components in SAS programming?
Answer: The 3 components in SAS programming are:
- Statements
- Variables
- Dataset
Q #3) Enlist the syntax rules followed in SAS statements.
Answer: SAS program is written in Editor Window. Here, it contains a series of statements followed by the proper syntax in an order for the SAS program to understand it.
Some of the syntax rules that are followed in the case of Statement component of SAS are as follows:
- The end of any statement is marked by a semicolon (;).
- A semicolon is also used to separate multiple statements that appear on a single line.
- SAS statements are not case sensitive and extra spacing before statements are automatically removed.
- Comments can be included in the SAS program for statements in two different ways as:
- A line beginning with an asterisk (*) and ending with a semicolon (;).
- A line beginning with a forwarding slash and an asterisk (/*) and ending with an asterisk and a forward slash (*/).
Q #4) What are the data types that SAS contains?
Answer: ‘Numeric’ and ‘Character’ are the two types of data types which the SAS program contains.
Q #5) What are PDV and their functions?
Answer: Program Data Vector (PDV) is a logical concept and is defined as an area of memory where a data set is being built by SAS.
Functions of PDV are as follows:
- A database having one observation at one time is created.
- The input buffer for holding the data from an external file is created at the time of compilation.
- PDV contains two automatic variables namely, _N_ (displays the count of the data step that is being executed) and _ERROR_ (notifies the error that occurs at the time of execution).
Q #6) What do you know about the SAS data set?
Answer: SAS data set is basically referred to as the data that is available for analysis within a SAS program. SAS dataset is also referred to as the SAS data table.
SAS data table consists of two parts:
- Columns of variables
- Rows of observations
Useful information about the SAS data set can be summarized as follows:
- SAS Dataset can read as well as it has built-in data sources for use like Excel, Access, etc.
- The dataset which is used only in the current session run and discarded after the session ends is known as Temporary Dataset.
- The Dataset that is stored for use in the future session is also known as the Permanent Dataset.
- The built-in data set can be accessed using this path Libraries -> My Libraries->SASHELP.
Q #7) Explain why double trailing @@ is used in Input Statements?
Answer: During data step iteration, including double trailing @@ in Input statements implies that SAS should hold the current record for the purpose of execution of the next Input statement rather than switching onto the new record.
Q #8) Explain the difference between NODUP and NODUPKEY options?
Answer: For removing duplicate values from the table, PROC SORT is basically categorized between two options:
- NODUP
- NODUPKEY
The difference between these two options can be seen below:
NODUPKEY
NODUP
Compares just the BY variable present in the dataset.
Compares all the variables present in the dataset.
Removes duplicate options for the values of variable listed in BY statement.
Identifies and eliminates duplicate observations.
Syntax:
PROC SORT DATA=readin NODUPKEY;
BY variable name;
RUN;
Syntax:
PROC SORT DATA=readin NODUP;
BY variable name;
RUN;
Q #9) Which command is used to perform sorting in the SAS program?
Answer: PROC SORT command is used for performing sorting, be it on a single variable or multiple variables. This command is performed on the dataset where the new data set is created as a result of sorting but the original data set remains unchanged.
Syntax:
PROC SORT DATA=original OUT=Sorted;
BY variable;
Where,
‘Original’ refers to the original dataset
‘Sorted’ refers to the result as sorted dataset
‘Variable’ refers to the column on which sorting operation is done.
Sorting can be done in both ascending as well as descending order.
For the dataset to display in descending order, keyword ‘Descending’ is used in the BY statement with the column name on which sorting is to be performed.
PROC SORT DATA=original OUT=Sorted;
BY DESCENDING variable
Q #10) Explain the difference between Informat and Format with an example.
Answer: The difference between Informat and Format can be explained as:
Informat
Format
Indicate SAS how to read data into SAS variable.
Indicate SAS how to display values in the variable.
These are used to read the data or take input data from external files.
These are used to write the data.
Q #11) Differentiate INPUT and INFILE.
Answer: Including an INFILE statement within the SAS programming identifies an external file that consists of the data, whereas including INPUT statement in SAS programming describes the variables used.
The syntax for INFILE:
INFILE ‘filename’;
The syntax for INPUT:
INPUT ‘varname1’ ‘varname2’;
Q #12) Explain the use of PROC print and PROC contents?
Answer: The PROC step of the SAS program is used to invoke built-in procedures for analyzing the data of the dataset.
PROC print: Ensures that the data present in the dataset are read correctly.
PROC contents: Displays the information about the SAS dataset.
Q #13) Explain DATA_NULL_?
Answer: As the name defines, DATA_NULL_ is a data step that actually does not create any data set.
It is used for:
- Creating macro variables.
- Writing the output without any data set.
Q #14) How is character variable converted into a numeric variable and vice versa?
Answer: Under SAS programming, there arise many tasks where a character value is to be converted into the numeric and in the same way, a numeric value is to be converted into a character value.
PUT() is used to convert numeric to character. In this case, the source format and source variable type must always be similar.
Example:
char_var= PUT( num_var, 6.);
INPUT() is used to convert a character to numeric. In this case, the source variable type must always be character variables.
Example:
Num_var= INPUT(char_var,2.0);
Q #15) What is the purpose of _CHARACTER_ and _NUMERIC_?
Answer: In the current dataset,
_CHARACTER_ defines all the character variables that are currently defined.
Example: To include all the character variables in PROC MEANS, the following statements are used:
PROC MEANS;
Var_character_;
Run;
_NUMERIC_ defines all the numeric variables that are currently defined.
Example: To include all the numeric variables in PROC MEANS, following statements are used:
PROC MEANS;
Var_numeric_;
Run;
Q #16) What commands are used in the case of including or excluding any specific variables in the data set?
Answer: DROP, KEEP, and data set options are used for this purpose.
The variable we want to remove from the data step is specified in the DROP statement.
The variable we want to retain from the data step is specified in the KEEP statement.
Q #17) Differentiate between PROC MEANS and PROC SUMMARY.
Answer: The difference between PROC MEANS and PROC SUMMARY can be understood as follows:
PROC MEANS
PROC SUMMARY
This procedure produces the printed report by default in the OUTPUT window.
This procedure includes the PRINT in the statement to produce the printed report.
PROC MEANS by default take all the numeric variables in the analysis.
PROC SUMMARY takes the variables into the statistical analysis that are described in VAR statement.
Q #18) Explain the purpose of SUBSTR functions in SAS programming.
Answer: In SAS programming, whenever there is a requirement of the program to abstract a substring, the SUBSTR function is used in the case of a character variable.
When a start position and length are specified, then this function is used for abstracting character string.
Syntax: SUBSTR(char_var, start,length);
Q #19) Name and describe few SAS character functions that are used for data cleaning in brief.
Answer: Few SAS character functions that are used for data cleaning are enlisted below:
- Compress(char_string) function is used for removing blanks or some specified characters from a given string.
- TRIM(str) function is used for removing trailing blanks from a given string.
- LOWCASE(char_string) function is used for converting all the characters in a given string to lowercase.
- UPCASE(char_string) function is used for converting all the characters in a given string to uppercase.
- COMPBL(str) function is used for converting multiple blanks to a single blank.
Q #20) Mention few ways with which a “table lookup’ is done in SAS programming.
Answer: In SAS programming, the table lookup values can be stored in the following ways:
- Code
- Array
- Hash object
- Format
- Dataset
The following techniques are used to perform ‘table lookup’ in SAS respectively:
- SELECT/WHEN or IF/THEN statements
- Array Index value
- Hash object key value
- FORMAT statement, PUT function
- Merge, join, KEY= Option
Let us see an example which shows the ‘Code’ way to perform table lookup by using ‘IF/THEN’ statements:
data location;
set myinfo;
if AreaCode='226' then Location='Ontario, Canada';
else if AreaCode='212' then Location='New York, NY';
else Location='Unknown';
run;
Q #21) Differentiate between CEIL and FlOOR functions.
Answer: CEIL function is used for truncating numeric values where it displays the output as the smallest integer. By smallest integer, here means the integer value is greater than/equal to the argument.
Example: CEIL(12.85) will display output as 13.
FLOOR function is used for truncating numeric values where it displays the output as the greatest integer. By greatest integer, here means that the integer value is less than/equal to the argument.
Example: FLOOR(12.85) will display output as 12.
Q #22) What are the ways in which Macro variables can be created in SAS programming?
Answer: Well a number of different techniques can be used to create macro variables in SAS programming.
Enlisted below are the five most commonly used methods:
- %LET statement
- Macro parameters (named as well as positional)
- %DO statement (iterative)
- INTO in PROC SQL
- CALL SYMPUTX routine
Q #23) Explain the purpose of the RETAIN statement.
Answer: As the meaning of the word ‘RETAIN’ signifies to keep the value once assigned, the purpose of RETAIN statement is the same in SAS programming as it’s meaning implies.
Within a SAS program, when it is required to move from the current iteration to the next of the data step, at that time RETAIN statement tells SAS to retain the values rather than set them to missing.
Example: Let us print a program that will display the output value of ‘z’ starting from 1 by using the RETAIN statement.
data abc;
set xyz;
RETAIN z 0;
z = z + 1;
run;
Q #24) Which command is used to save logs in the external file?
Answer: PROC PRINTTO command is used to save logs in the external file.
Example:
PROC PRINTTO log="C:\Users\abc\Downloads\LOG11.txt" new;
run;
Q #25) Mention some common errors that are usually committed in SAS programming.
Answer: Enlisted below are some of the common errors which are usually committed especially when you are new to this programming language.
- The basic syntax includes a semicolon at the end of each statement and missing a semi-colon is the most common mistake.
- You skip checking the logs after submitting the program.
- Commenting errors like failing to use comments where necessary or using comments in an inappropriate way.
- Not using proper debugging methods.
Q #26) Mention SAS system options to debug SAS macros.
Answer: To help in tracking the macro code as well as the SAS code generated by the macros, some system options can be used.
They are:
- MLOGIC
- MPRINT
- SYMBOLGEN
The message that will be generated by these system options can be seen in the SAS log.
Q #27) Differentiate between SAS functions and SAS procedures.
Answer: The major differences can be discovered/understood by the case explained for both SAS functions and Procedures.
Case:
For Function, argument value is supplied or say taken for calculation across the observation mentioned in the program statement whereas, in the case of Procedure, every observation is expected to have only one variable through which calculation is done as mentioned in the below example.
Let us understand it with examples:
data average;
set temp;
avgtemp = mean( of T1 – T24 );
run;
Here in the above examples, the arguments passed to the mean function are taken for calculation as an observation.
proc sort;
by month;
run;
proc means;
by month;
var avgtemp;
run;
Here in the above example, Proc means function calculates the average temperature for one argument that is passed as an observation i.e. by month.
Q #28) What do you know about SYMPUT and SYMGET?
Answer: The major differences between the two are mentioned below.
SYMPUT is used for storing the value of a data set into the macro variable whereas SYMGET is used for retrieving the value from the macro variable to the data set.
Q #29) Explain the special input delimiters used in SAS programming.
Answer: The special input delimiters used in SAS programming are:
- DLM
- DSD
They are used in the statement ‘INFILE’ and DSD has the functionality of ignoring the delimiters that appear enclosed in quotation marks.
Q #30) Which function is used to count the number of intervals between two SAS dates?
Answer: Interval function INTCK is used for counting the number of intervals between two given SAS dates.
Syntax:
INTCK(interval,start-of-period,end-of-period)
- A line beginning with an asterisk (*) and ending with a semicolon (;).
- A line beginning with a forwarding slash and an asterisk (/*) and ending with an asterisk and a forward slash (*/).
PROC SORT DATA=readin NODUPKEY;
BY variable name;
RUN;
PROC SORT DATA=readin NODUP;
BY variable name;
RUN;
‘Original’ refers to the original dataset
‘Sorted’ refers to the result as sorted dataset
‘Variable’ refers to the column on which sorting operation is done.
Course Batch Timings
Course Features
Live Instructor Led Course
100-120 hrs of Class room or Online Live Instructor-led Classes conducting by industry domain specific professionals with lab support. Weekday class: 50 sessions of 2 hours each. and Weekend class:32 sessions (16 weekends) of 3 hours each.
Live project or Real-life Case Studies
Live project based on any of the selected use cases, involving DATA SCIENCE.
Assignments
Each class will be followed by practical assignments and interview questions which can be completed before the next class.
24 x 7 Expert Support
We have 24x7 offline and online support team available to help you with any technical queries you may have during the course or After the course.
Batch Flexibility
Yes, you have batch flexibility here. Once you join in Stansys you can attend classes in any batch or N number of batches within 1 year with same faculty.
Course Certificate
Yes, we will provide you the certificate of the attended software training course or to download (Certificate.pdf) soft copy version to their personal e-mail id (Who is attended training with us).
1 Year validity
You get 1-year validity for live classes (classroom/online) and lifetime access to the Learning Management System (LMS). Class recordings and presentations can be viewed online from the LMS.
Money back guarantee
You can cancel your enrolment within 7 working days. We provide you complete refund after deducting the administration fee(Rs.500/-).
Forum
We have a community forum with students and industry professionals for all our customers wherein you can enrich their learning through peer interaction and knowledge sharing.
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24*7 Server Support is Avialable
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