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Skills measured
- Design and implement a data warehouse (10–15%)
- Load data (25–30%)
- Configure and deploy SSIS solutions (20–25%)
- Extract and transform data (20–25%)
- Build data quality solutions (15–20%)
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.
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
Reference: https://www.microsoft.com/en-us/learning/exam-70-463.aspx
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Languages: English, Chinese (Simplified), French, German, Japanese, Portuguese (Brazil)
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.
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Microsoft 070-463 Exam Syllabus Topics:
| Section | Objectives |
|---|---|
| Topic 1: Optimize and maintain a data warehouse | - Performance tuning and query optimization - Monitor and troubleshoot ETL processes - Implement security and access control |
| Topic 2: Build and deploy multidimensional models | - Define measures, dimensions, and hierarchies - Design and implement cubes using SSAS - Implement OLAP storage and processing |
| Topic 3: Build data warehouse infrastructure | - Configure SQL Server Integration Services (SSIS) - Implement SQL Server Agent jobs |
| Topic 4: Design and implement data warehouse | - Design logical and physical data warehouse schema - Design fact and dimension tables - Implement indexing and partitioning strategies |
| Topic 5: Extract, transform, and load data | - Develop ETL solutions using SSIS - Manage incremental data loads - Implement data cleansing and data flow transformations |
