CERTIFICATES

In this module, students delve into working with cubes and dimensions in SSAS (SQL Server Analysis Services). They learn to design, create, and manage multidimensional structures like cubes and dimensions for analytical purposes. The curriculum emphasizes building data models, defining hierarchies, and utilizing SSAS for advanced analytics and reporting, empowering students with multidimensional data manipulation skills.

In this module, students learn techniques for attribute sorting and grouping in SSAS to enhance data organization. Additionally, the curriculum covers Slowly Changing Dimensions (SCDs) strategies, enabling the management of changing data over time within dimensional structures.

Within this module, students delve into handling measures and measure groups in SSAS (SQL Server Analysis Services). They learn to define, manage, and optimize measures, which quantify data for analysis. The curriculum emphasizes designing and organizing measure groups, enabling students to proficiently manage and utilize quantitative data within SSAS for comprehensive analysis and reporting purposes.

This module introduces MDX (Multidimensional Expressions), teaching students the syntax and principles behind querying multidimensional data. It covers MDX basics, enabling students to construct queries for retrieving and analyzing data within SSAS environments.

This module guides students in incorporating calculations into SSAS cubes, covering the creation and implementation of custom calculations within multidimensional models. It focuses on adding calculated members, measures, and KPIs to enhance data analysis and reporting capabilities within the SSAS environment.

This module explores customizing cube functionality, teaching students to tailor SSAS cubes by implementing advanced features like perspectives and translations. It covers implementing actions to create interactive experiences and navigation within cubes, enhancing user interaction and data exploration capabilities.

This module covers creating perspectives to tailor cube views and translations for multilingual support in SSAS. Students learn to customize data visibility and facilitate multilingual analysis by organizing cube views and implementing translations within SSAS environments.

This module focuses on building a tabular data model using SQL Server Analysis Services (SSAS). Students learn to create tabular models, define relationships, and optimize data for efficient analysis and reporting. The curriculum covers designing data models, defining measures, and utilizing SSAS to create tabular structures for streamlined data analysis within SQL Server environments.

In this module, students learn to construct tabular data models using SQL Server Analysis Services (SSAS), focusing on model design and relationship definition. They explore measures, entity relationships, and utilize SSAS tools to create efficient data structures for analysis and reporting in SQL Server environments.

This module introduces Data Analysis Expressions (DAX), covering its role in formulating calculations and queries within tabular models in SQL Server Analysis Services (SSAS). Students learn the syntax and functionalities of DAX, enabling them to create calculated columns, measures, and manipulate data efficiently for analysis and reporting purposes.

This module instructs students on leveraging Data Analysis Expressions (DAX) within SQL Server Analysis Services (SSAS) to craft calculated columns and measures. They learn to create custom calculations, derive new column values, and define aggregated measures, enhancing data manipulation and analysis capabilities within tabular data models.

Performing Predictive Analysis with Data Mining involves utilizing algorithms and techniques within SQL Server Analysis Services (SSAS) to uncover patterns and make predictions from data. Students learn to apply data mining models to historical data, discovering trends, correlations, and predictive insights.

Creating a Custom Data Mining Solution involves designing and implementing tailored data mining models within SQL Server Analysis Services (SSAS). Students learn to build custom data mining algorithms, define specific parameters, and optimize models for unique business requirements.