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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.

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

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

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

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

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.

  • 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.
  • Use %INPUT statement.
  • Use the SYMPUT and SYMPUTX routine in the DATA Step.
  • Use %GLOBAL statement.
  • Use INTO clause of the SELECT statement in SQL.

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

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

Understand the use of macro functions.

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

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

  • Trace the flow of execution with MLOGIC.
  • 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.

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

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

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

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

  • Define a SAS function

Perform effective benchmarking.

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

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

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

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SASInstitute A00-212日本語 Exam Syllabus Topics:

SectionObjectives
SQL Processing with SAS- Joining tables and subqueries
- PROC SQL queries
Advanced Data Manipulation- Data transformation techniques
- DO loops and iterative processing
- Array processing
Data Transformation and Reporting- Formatting and informats
- Generating reports using SAS procedures
Data Access and Management- Data step processing and control logic
- Reading and importing data from external sources
- Combining and restructuring data sets
Macro Language Processing- Macro variables and resolution
- Macro programs and automation

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