A00-212 : SAS Advanced Programming for SAS 9 Certified Professional salary

The average salary of a A00-212 : SAS Advanced Programming for SAS 9 Certified Expert in

• Europe - 45,347 EURO
• United State - 70,247 USD
• India - 8,42,327 INR
• England - 46,632 POUND

Reference: https://www.sas.com/en_us/certification/credentials/foundation-tools/advanced-programmer.html

A00-212 : SAS Advanced Programming for SAS 9 Certification Path

The A00-212 : SAS Advanced Programming for SAS 9 Certification is one of the highest level of certification mainly focussing to the Advanced Programming concepts.

if you pass your exam and meet all requirements for a credential, you will receive an e-mail from SAS within 72 business hours with instructions providing access to your certificate and logo through the SAS Certification Manager. You will also receive an email from Acclaim with access to your digital badge. For questions regarding access to either of these, please visit SAS Website.

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Topics of A00-212 : SAS Advanced Programming for SAS 9 Exam

Candidates must know the exam topics before they start of preparation. because it will really help them in hitting the core. Our A00-212 : SAS Advanced Programming for SAS 9 Dumps will include the following topics:

1. Accessing Data Using SQL

Generate detail reports by working with a single table, joining tables, or using set operators in the SQL procedure.

• Use the SELECT statement.
• Retrieve rows that satisfy a condition.
• Select columns in a table.
• Create new columns.
• Sort data.
• Join tables - inner joins, full joins, right joins, left joins.
• Combine tables using set operators - union, outer join, except, intersect.
• Validate a query.

Generate summary reports by working with a single table, joining tables, or using set operators in the SQL procedure.

• Group data.
• Summarize data.
• Filter grouped data.

Construct sub-queries and in-line views within an SQL procedure step.

• Subset data by using correlated subqueries.
• Reference an in-line view with other views or tables (multiple tables).
• Subset data by using non-correlated subqueries (HAVING clause).

Compare solving a problem using the SQL procedure versus using traditional SAS programming techniques.

• Create SAS Data sets (tables).
• Alter columns attributes.
• Delete a table.
• Delete rows.
• Update data values in a table.
• Create an index.
• Use SAS data set options with PROC SQL.
• Use PROC SQL with the SAS Macro Facility.
• Insert rows into tables.

Access Dictionary Tables using the SQL procedure.

• Use the DESCRIBE TABLE statement.
• Access SAS system information by using DICTIONARY tables.

2. Macro Processing

Create user-defined and automatic macro variables within the SAS Macro Language.

• Use the SYMPUT and SYMPUTX routine in the DATA Step.
• Use INTO clause of the SELECT statement in SQL.
• Use %INPUT statement.
• Use %GLOBAL statement.
• Define Macro variables.
• Use the SYMGET function to return the value of a macro variable to the DATA step during DATA step execution.
• Use %LOCAL statement.

Automate programs by defining and calling macros using the SAS Macro Language.

• Insert comments into macros.
• Use the %MACRO statement.
• Pass information into a macro using parameters.
• Define a macro.
• Generate SAS Code conditionally by using the %IF-%THEN-%ELSE macro statements or iterative %DO statements.

Understand the use of macro functions.

• Insert comments into macros.
• Use the %MACRO statement.
• Pass information into a macro using parameters.
• Define a macro.
• Generate SAS Code conditionally by using the %IF-%THEN-%ELSE macro statements or iterative %DO statements.

Use various system options that are available for macro debugging and displaying values of user-defined and automatic macro variables in the SAS log.

• Examine the generated SAS statements with MPRINT.
• Use system options to track problems.
• Examine macro variable resolution with SYMBOLGEN.
• Use the %PUT statement to track problems.
• Trace the flow of execution with MLOGIC.

Create data-driven programs using SAS Macro Language.

• Create macro variables with a list of values.
• Use indirect reference to macro variables.
• Generate repetitive macro calls using the %DO loop, macro variable, and the EXECUTE routine.

3. Advanced Programming Techniques

Demonstrate the use of advanced data look-up techniques such as array processing, hash objects, formats, and merging.

• Combine data using multiple set statements with KEY= option.
• Compare DATA step match-merge and PROC SQL joins.
• Create custom formats with the PICTURE statement.
• Manage custom formats with FMTSEARCH= system option.
• Use hash objects as lookup tables.
• Combine data conditionally using multiple set statements.
• Use formats to create data via lookups.
• Process data with multi-dimensional arrays.
• Combine multiple data sets using FILEVAR= option.

Reduce computing resource requirements by controlling the space required to store SAS data sets.

• Reduce length of numeric variables.
• Use compression techniques, RLE (Run-Length Encoding) and RDC (Ross Data Compression).
• Use SAS views.
• Eliminate variables and observations.

Use the FCMP procedure to create a user-defined function.

• Define a SAS function

Perform effective benchmarking.

• Understand resources related to efficiency.
• Interpret the resulting resource utilization statistics for the Z/OS environment and for directory based OS.
• Use SAS System options to track resources.

Use SAS indexes.

• Create and delete indexes using the DATA step, the DATASETS procedure, or the SQL procedure.
• Identify appropriate applications for using indexes.

Compare techniques to eliminate duplicate data.

• Use the DATA step.
• Use the SQL procedure.
• Use the SORT procedure.

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