Exam 70-463: Implementing a Data Warehouse with Microsoft SQL Server 2012/2014
This exam is primarily intended for ETL and data warehouse developers who create Business Intelligence (BI) solutions, and whose responsibilities include data cleansing, and Extract Transform Load and data warehouse implementation.
Part of the requirements for: MCSA: SQL Server 2012/2014
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This exam is primarily intended for ETL and data warehouse developers who create Business Intelligence (BI) solutions, and whose responsibilities include data cleansing, and Extract Transform Load and data warehouse implementation.
High level topics covered by our practice test
This Web Simulator is for Microsoft DBA which are database professionals who perform Data Wherehouse study, maintenance, and configuration and performance tuning tasks when defining Data Wherehouse dimensions and fact tables. Students responsibilities include setting up Data Wherehouse systems, making sure those systems operate efficiently and fast, and regularly manage and Implement SSIS package.
Reference: https://www.microsoft.com/en-us/learning/exam-70-463.aspx
Our 70-463 exam dumps will include those topics:
- Build data quality solutions (15-20%)
- Design and implement a data warehouse (10-15%)
- Configure and deploy SSIS solutions (20-25%)
- Load data (25-30%)
- Extract and transform data (20-25%)
For more info visit: Microsoft Official 70-463 Exam Reference
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Microsoft 070-463 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Configure and deploy SSIS solutions | 20-25% | - Secure and manage SSIS environments - Configure SSIS packages and parameters - Deploy SSIS projects and packages - Implement logging and debugging |
| Design and implement a data warehouse | 10-15% | - Design for scalability and performance - Design and implement indexes and partitions - Design dimensions and fact tables - Implement star and snowflake schemas |
| Extract and transform data | 20-25% | - Implement lookups and fuzzy grouping - Design and implement data flows - Handle data types and errors - Apply transformations and aggregations |
| Load data | 25-30% | - Manage incremental loads - Implement transactions and checkpoints - Design and implement control flow - Use bulk load operations |
| Build data quality solutions | 15-20% | - Clean and standardize data - Implement Data Quality Services (DQS) - Match and deduplicate data - Integrate DQS with SSIS |
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