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Business Intelligence Developer

Analyzing Data with Excel

Module 1: Introduction to Business Intelligence
Understanding Business Intelligence (BI) concepts. Overview of BI tools and technologies. Importance and benefits of BI in business decision-making.
Module 2: SQL Server Integration Services (SSIS)
Introduction to SSIS. Creating and managing SSIS packages. Data extraction, transformation, and loading (ETL) processes. Handling data flow and control flow tasks. Implementing error handling and logging in SSIS packages.
Module 3: SQL Server Analysis Services (SSAS)
Introduction to SSAS. Creating and managing OLAP cubes. Understanding dimensions, hierarchies, and measures. Implementing data mining models. Processing and deploying SSAS projects.
Module 4: SQL Server Reporting Services (SSRS)
Introduction to SSRS. Designing and creating reports. Implementing report parameters and expressions. Configuring and deploying reports. Managing and securing reports.
Module 5: Data Warehousing
Concepts of data warehousing. Designing a data warehouse. Implementing star and snowflake schemas. ETL processes for data warehousing. Maintaining and optimizing data warehouses.
Module 6: Power BI
Introduction to Power BI. Connecting to various data sources. Creating interactive dashboards and reports. Implementing data models and DAX (Data Analysis Expressions). Sharing and collaborating on Power BI content.
Module 7: Data Modeling and Analysis
Principles of data modeling. Designing relational and multidimensional data models. Implementing data relationships and constraints. Analyzing data using MDX (Multidimensional Expressions) and DAX. Optimizing data models for performance.
Module 8: Performance Tuning and Optimization
Techniques for optimizing BI solutions. Indexing strategies for data warehouses. Query optimization and tuning. Monitoring and troubleshooting BI performance. Best practices for efficient BI solution development.
Module 9: Advanced Data Analytics
Introduction to advanced analytics and machine learning. Implementing predictive analytics in SSAS. Using R and Python for data analysis in SQL Server. Developing and deploying advanced analytics models. Integrating advanced analytics with BI solutions.
Module 10: Security and Compliance
Ensuring data security in BI solutions. Implementing role-based security in SSAS and SSRS. Managing data permissions and access controls. Compliance considerations and data privacy. Auditing and monitoring BI environments.
Module 11: Project Management for BI
Planning and managing BI projects. Gathering and analyzing business requirements. Designing BI solutions to meet business needs. Managing project timelines and resources. Ensuring quality and successful delivery of BI projects.

This summary provides a comprehensive overview of the key topics and skills covered in the Microsoft diploma “Business Intelligence Developer,” focusing on the essential aspects of designing, developing, and managing BI solutions using Microsoft tools and technologies.

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