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Microsoft Business Intelligence architecture. Data Modeling, Representation, and Transformation for BI.
Concepts of OLAP database and tables in SSAS. Generating and processing new data sources and new Cubes
Concepts of Multidimensional Modeling, ETL, and Transformations in SSIS
SSIS, SSAS, and SSRS architecture and their components. Sample of data flow across components.
Defining various relationship types in SSAS. Preparing for MCSE: Business Intelligence Certification Exam
Building and creating charts, reports, and dashboards with SSRS
Exam 70-767 Implementing a SQL Data Warehouse(SSIS)
Introduction to Data Warehousing
Planning Data Warehouse Infrastructure
Designing and Implementing a Data Warehouse
Column store Indexes
Implementing an Azure SQL Data Warehouse
Creating an ETL Solution
Implementing Control Flow in an SSIS Package
Debugging and Troubleshooting SSIS Packages
Implementing a Data Extraction Solution
Enforcing Data Quality
Master Data Services
Extending SQL Server Integration Services
Deploying and Configuring SSIS Packages
Consuming Data in a Data Warehouse
Exam 70-768 Developing SQL Data Models (SSAS)
Business Intelligence & Data Modelling
Creating Multidimensional Databases
Working with Cubes and Dimensions
Working with Measures and Measure Groups
Introduction to MDX
Customizing Cube Functionality
Tabular Data Model by Using Analysis Services
Introduction to Data Analysis Expression (DAX)
Performing Predictive Analysis with Data Mining
Exam 70-466: Implementing Data Models and Reports with Microsoft SQL Server(SSRS)
Introduction to Business Intelligence and Data Modeling
Creating Multidimensional Databases
Working with Cubes and Dimensions
Working with Measures and Measure Groups
Introduction to MDX
Customizing Cube Functionality
Implementing an Analysis Services Tabular Data Model
Introduction to Data Analysis Expression (DAX)
Implementing Reports with SQL Server Reporting Services
Automating Report Execution and Delivery
Delivering BI with SharePoint PerformancePoint Services
Performing Predictive Analysis with Data Mining