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SASInstitute A00-260 Exam Overview:
| Certification Vendor: | SAS Institute |
| Exam Name: | SAS Data Integration Development |
| Exam Number: | A00-260 |
| Exam Format: | Multiple choice, Scenario-based questions |
| Exam Price: | USD 180-220 |
| Real Exam Qty: | 50-60 |
| Certificate Validity Period: | Not formally specified (SAS certifications may not expire or may be subject to program updates) |
| Passing Score: | 70% |
| Exam Duration: | 110-120 |
| Related Certifications: | SAS Certified Base Programmer for SAS 9 SAS Certified Data Integration Developer SAS Platform Administration |
| Available Languages: | English |
| Sample Questions: | SASInstitute A00-260 Sample Questions |
| Exam Way: | Computer-based exam delivered via Pearson VUE testing centers or online proctoring (where available) |
| Pre Condition: | Recommended experience with SAS Base Programming and familiarity with ETL/data warehousing concepts |
| Official Syllabus URL: | https://www.sas.com/en_us/certification.html |
There are topics of SAS Certified Data Integration Developer (A00-260) Exam
Candidates must know the exam topics before they start of preparation. Because it will really help them in hitting the core. Our SAS Certified Data Integration Developer A00-260 exam dumps will include the following topics:
Overview
- Describe the available interfaces
- Define the architecture of the platform for SAS Business Analytics
- Discuss the DataFlux Data Management Server
- Define the change management feature of SAS Data Integration Studio
Creating Metadata for Source and Target Data
- Register metadata for a comma-delimited external file.
- Define administrative tasks to be performed for SAS Data Integration Studio.
- Import and Export Metadata.
- Use Register Tables wizard to register source data.
- Describe the New Library Wizard.
Creating Metadata for Target Data and Jobs
- Describe features of the New Table wizard.
- Define Impact and Reverse Impact Analysis.
- Investigate mapping and propagation.
- Work with performance statistics.
- Generate reports on metadata for tables and jobs.
- Discuss components of Join's Designer window
- Import SAS code.
Working with Transformations
- Discuss and use the Compare Tables transformation.
- Discuss and use the Loop transformations.
- Apply and use the Standardize with Definition transformation.
- Discuss and use transformations in the SQL grouping of transformations.
- Explain the functionality of the Data Validation transformation.
- Discuss and use the Extract and Summary Statistics transformation.
- Investigate where status handling is available.
- Discuss and use the Rank, Transpose, Append, List and Sort transformations.
- Discuss and use the Apply Lookup Standardization transformation.
Working with Tables and the Table Loader Transformation
- Discuss reasons to use the Table Loader transformation.
- Discuss various types of keys and how to define in SAS Data Integration Studio.
- Discuss the Bulk Table Loader transformation.
- Discuss various load styles provided by the Table Loader transformation.
- Discuss indexes and how to define in SAS Data Integration Studio.
- Discuss Table Loader options for keys and indexes.
- Discuss and use the components of the Join's Designer Window related to in-database processing.
Working with Slowly Changing Dimensions
- Discuss the Lookup transformation.
- Discuss the SCD Type 1 Loader.
- Detect and track changes.
- List the functions of the SCD Type 2 transformation.
- Define business keys.
Defining Generated Transformations
- Define SAS code transformation templates.
- Create a custom transformation
Deploying Jobs
- Describe deployment of SAS Data Integration Studio jobs as a SAS Stored Process.
- Discuss batch servers.
- Discuss the types of job deployment available for SAS Data Integration Studio Jobs.
- Provide an overview of the scheduling process.
- Discuss the Schedule Manager in SAS Management Console.
- Discuss the types of scheduling servers.
In Database Processing
- Define and discuss ELT methods
- Define in-database processing
- Use a DBMS function in a SAS DI job
- Enable in-database processing
Reference: https://www.sas.com/en_us/certification/credentials/data-management/data-integration-developer.html
There are some steps to apply for SAS Certified Data Integration Developer (A00-260) Exam
In order to apply for the SAS Certified Data Integration Developer (A00-260), You have to follow these steps
- Step 1: Visit to Pearson Exam Registration
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- Step 3: Search for SAS Certified Data Integration Developer (A00-260) Exam Certifications Exam
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SAS Certified Data Integration Developer (A00-260) Exam Reference
How can you ready for SAS Certified Data Integration Developer (A00-260) Certification Exam
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SAS Data Management certification is considered the point of reference for knowledge, skills and proven ability to create metadata for source and target data, create metadata for target data and jobs and use transformations. SAS® Certified Data Integration Developer certification is a very important Certification in the SAS Institute certification hierarchy. SAS Institute A00-260 SAS Certified Integration Developer for SAS exam scores confirm that you have a solid knowledge base in data management and SAS data management support. To do this, you must pass the SAS Institute A00260 Data Integration Developer Institute Certificate for the SAS exam. A00-260 (SAS Certified Data Integration Developer for SAS) is one of the data management exams you must pass to obtain the SAS Data Management certification.
SASInstitute A00-260 Exam Syllabus Topics:
| Section | Objectives |
|---|---|
| Topic 1: Data Integration Concepts | - ETL architecture and workflows - Data integration principles and best practices |
| Topic 2: SAS Data Integration Studio | - Metadata management and repositories - Project creation and job flows |
| Topic 3: Job Scheduling and Automation | - Scheduling ETL jobs - Monitoring and troubleshooting job execution |
| Topic 4: Performance and Administration | - Security and access control in SAS environments - Performance tuning of ETL processes |
| Topic 5: Data Transformation and Processing | - Using transformations and process flows - Data extraction, transformation, and loading (ETL) |
| Topic 6: Data Quality and Management | - Data cleansing and validation - Handling data inconsistencies and errors |
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