SAS (Statistical Analytics System) is a popular tool for Data Analytics and this is pretty easy to learn especially for those people who know SQL already. SAS is one of the leading including R and Python and works amazingly when it comes to handling a large amount of data and options for parallel computation. If you will look at the SAS job trends then it covers approx. 70% data analytics market and R is covering only 15 percent of the total market share.
So, if you are a tech-savvy and wanted to hire as a SAS expert then this blog is a perfect guide for you to learn all important questions that may be asked during a SAS interview. The questions are segregated based on the difficulty level and you can pick the most relevant section as per your expertise to reap the maximum benefits from this post. This blog is one-stop solutions where you will find the maximum number of questions to boost your interview preparation.
This is the most expected question asked by interviewers if you are a fresher. This is a software suite that is mainly needed for data analytics, business intelligence, data management, multivariant analysis, predictive analysis, etc. The concept was introduced by the SAS Institute and provides an interactive graphical user interface with plenty of advanced options by SAS language. The interface can be quickly accessed by non-technical users too and easy to learn by anyone.
Here is a list of reasons that will explain to you why should you choose SAS over other data analytics tools –
The tool can provide the following benefits for your business –
The SAS framework has four capabilities, these are Analyze, Access, Manage, and Present.
To save the summary statistics in a SAS dataset, Output statement is needed. This information can be used further for creating more customized reports.
To break the processing of current data sets quickly, the STOP statement is needed.
If you are interested in processing a certain set of variables and don’t want to appear then in the new dataset then the “drop = dataset” option is used in the set statement.
If you are not interested in processing a certain set of variables and don’t want to appear then in the new dataset then the “drop = dataset” option is used in the data statement.
When data is accessed from some external file then only observations are considered and variables need to declare again if you want to use them.
If you wanted to access data from the existing dataset then use the SET statement and values of variables will be retained from one observation to another.
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They are divided into two categories majorly – Character and Numeric.
In the case of functions, the values of arguments are supplied across an observation. In the case of procedures, there is only one given to each variable.
Sum function will return the total of non-missing arguments and the “+” operator returns the missing value of any argument value is left behind.
To read the last value from an unsorted dataset to appear in the new data set, end = data set option is used in SAS.
When dollar ($) sign is added before a variable, the conversion process is blocked by the dollar sign and it is not covered to numeric values later.
Proc Means produce statistics for subgroup only if it is sorted first. At the same time, Proc Summary can produce statistics for all groups automatically.
To delete the duplicates values in a dataset, use the “Proc SQL” command.
First of all, it will scan each statement for syntax errors. Now, it will decide how the SQL query should be executed in SAS. A particular table is loaded into the data engine and related calculations are performed. After this, the final table is created in the memory and it is sent to the OUTPUT table described in the SQL.
For numeric to character conversion, put function is used. For the character to numeric conversion, the input function is used.
This is 200
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To remove the repeated occurrence of a pattern of characters within a character string, TRANWRD function is used in SAS.
Scan, Trim, tranwrd, Catx, Substr, Index, Find, Sum.
|Date||SAS Date Value|
|January 1, 1959||-365|
|January 1, 1960||0|
|January 1, 1961||366|
|January 1, 2003||15706|
Dates in SAS
A SAS date is a numeric value equal to the number of days since January 1, 1960. Also, there are plenty of tools that can be used to read printed data in SAS datasets.
Data finance; Amount=1000; Rate=.075/12; Do month=1 to 12; Earned +(amount+earned)*(rate); Output; End; Run;
Here, the total number of observations would be 12.
Do While the option is executed at the beginning of Do loop, if the result is false then it will never be executed again. At the same time, Do Until option is used at least once.
It can be done by doing while and do until options in SAS.
data work; do i=1 to 20 until(sum>=200000); year+1; sum+2000; sum+sum*.10; end; run;
Here, the do loop will run until the sum does not become greater than or equal to 20000 or until the loop executes 10 times as per the given program.
Here is the general syntax is given for the scan function in SAS –
Here, arguments will define the expression that you wanted to scan, n will specify the total number of characters to read, and delimiters will specify how characters will be enclosed in a single quotation.
No, it should be defined as the character data type only.
Yes, it depends on how variables are used within a SAS program
The length can go up to 32,767 variables for a dataset in SAS.
They are generally different by each other but there are certain conditions when meaning for both the options is the same as well.
They are the same for variable/columns in position order and rows ordered as they appear in the data set.
The trailing @ option is used in column pointer to hold the line. At the same time, the trailing @ @ option is used to hold the line even more strongly.
When the variables are declared as the group variables then rows with the same values will be collapsed. At the same time, order variables are used to create summary reports and group variables are used for list reports.
These are the mean, standard deviation, n count, maximum, or minimum values etc.
Use proc report and define the variable as group variable to create the summary report.
Define the MAXDEC= option, and you are done.
The Class Statement can be applied to any data set even if values are sorted properly or not.
For the BY Statement, vales must be first sorted before you use it.
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In the case of the Proc Means, reports are generated by default. On the other hand, you should use the Print option to generate a report in Proc Summary.
It can be done by Table Statement.
PROC FREQ is used for category variables and Proc Means is used for numeric variables in SAS.
TABLES variable-1*variable-2 <*…..variable-n>/ LIST;
merge data1 data2;
The job of interleaving operation is to combine independent multiple sorted data sets into a single combined dataset.
set data1 data2;
With this code, the dataset can be sorted and combined together.
Well, as per my experience, I will recommend using a one-to-one merge option than the match-merge option.
To add one dataset at the end of another dataset, the Append procedure is used in SAS.
Q49). Which procedure is used to analyze the data deeply?
Well, you can BMDP procedure here for data analysis.
The variable is suitable for elementary numerical analysis and how well the data is distributed across datasets.
This blog “SAS Interview Questions for Freshers, Intermediates, and the advanced workforce” gives you a sound idea of questions that are usually asked by interviewers and help you in passing the interview during the first attempt. This list is not enough but you should consider taking online SSIS training or Learn SAS for free by availing our self-learning courses at a huge discount with JanBask Training.
Moreover, if you are not sure of online training classes and its benefits, register for a demo class and clear all your doubts by interacting with certified mentors during the LIVE session. On the completion of the SSIS online training, you will learn to swim in the career pool of database tools and how they can be used for robust data management. All the Best!
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