Course Introduction
The SQL Server Analysis Services (SSAS) and Multidimensional Data Analysis Training Course is designed to develop the technical and analytical capabilities required to build, manage, and utilize enterprise analytical models using Microsoft SQL Server Analysis Services. Organizations increasingly depend on consolidated information to understand business performance, identify trends, evaluate operational results, and support strategic decisions. This course provides a practical understanding of how SSAS transforms large volumes of organizational data into structured analytical models that enable users to explore information from multiple dimensions and generate meaningful business insights.
The programme introduces participants to the architecture, concepts, and development environment of SQL Server Analysis Services, with particular emphasis on multidimensional data modeling and Online Analytical Processing (OLAP). Participants will examine the differences between transactional databases and analytical systems, understand the role of data warehouses, and explore how dimensions, measures, hierarchies, and measure groups are used to organize business information. The course explains how multidimensional models support analytical queries, consolidated reporting, and interactive exploration of organizational data across different business perspectives.
A major component of the training focuses on designing and developing multidimensional analytical models. Participants will learn how to create Analysis Services projects, establish data sources and data source views, define dimensions and attributes, construct hierarchies, and configure measure groups and cubes. They will examine relationships between fact and dimension tables, dimension usage, attribute relationships, and aggregation design. Practical exercises will demonstrate how to build analytical structures for financial performance, sales analysis, inventory management, procurement monitoring, customer behavior, and organizational performance measurement.
The course also explores advanced multidimensional analysis using MDX (Multidimensional Expressions), the query language used to retrieve and calculate information from multidimensional models. Participants will develop skills in querying cube data, creating calculated members, defining named sets, applying filters, and performing time-based comparisons. They will learn how to analyze year-to-date performance, cumulative results, growth rates, rankings, and other business indicators. The programme also examines processing strategies, partition management, aggregation design, and optimization techniques that improve the accuracy, responsiveness, and scalability of analytical solutions.
Effective analytical systems require appropriate security, governance, maintenance, and integration with enterprise reporting platforms. Participants will therefore examine role-based security, dimension and cell permissions, processing schedules, backup and recovery, deployment, and troubleshooting. The training also considers the relationship between multidimensional SSAS and tabular modeling, as well as integration with SQL Server data warehouses, Excel, SQL Server Reporting Services, and Power BI where supported by the relevant environment. Contemporary issues such as hybrid data architectures, cloud analytics, self-service business intelligence, and evolving Microsoft analytical technologies will provide additional context for enterprise implementation.
By the end of the training, participants will be able to design, develop, query, administer, and maintain multidimensional analytical solutions using SQL Server Analysis Services. They will understand how to transform warehouse data into reusable analytical models, enable interactive exploration, and produce consistent measures for enterprise reporting and decision support. The skills acquired will help organizations improve analytical performance, strengthen data-driven management, reduce repetitive reporting activities, and provide decision-makers with reliable information for evaluating results and identifying opportunities for improvement.
Duration
5 days
Who Should Attend
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Business intelligence developers responsible for developing enterprise analytical models and OLAP solutions.
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SQL Server database administrators involved in managing analytical databases and SSAS environments.
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Data warehouse developers responsible for preparing dimensional data structures for analytical processing.
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Data engineers working with enterprise data integration and analytical modeling solutions.
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Business intelligence analysts who use multidimensional models for organizational reporting and analysis.
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Data analysts seeking advanced skills in multidimensional data analysis and MDX querying.
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Database developers responsible for designing fact tables, dimension tables, and analytical data structures.
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Financial analysts developing multidimensional models for budgeting, forecasting, and financial performance analysis.
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Management information systems officers responsible for enterprise reporting and analytical information systems.
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Power BI and reporting developers working with Analysis Services models and enterprise semantic layers.
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Business analysts involved in defining analytical requirements, business measures, and performance indicators.
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Monitoring and evaluation specialists analyzing organizational results across programmes, departments, and reporting periods.
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IT professionals responsible for implementing and supporting Microsoft business intelligence technologies.
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Business intelligence consultants supporting data warehouse and enterprise analytics projects.
Course Objectives
By the end of this course, participants will be able to:
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Explain the architecture, components, and capabilities of SQL Server Analysis Services and distinguish multidimensional analytical systems from transactional database environments.
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Design multidimensional data models using fact tables, dimension tables, measures, hierarchies, attributes, and measure groups to support enterprise analytical requirements.
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Develop SSAS projects by configuring data sources, data source views, dimensions, cubes, and relationships for structured business intelligence applications.
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Create and manage multidimensional cubes with appropriate dimension usage, attribute relationships, measure definitions, and aggregation designs for efficient analytical processing.
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Apply MDX queries and expressions to retrieve analytical information, create calculated members, define named sets, and investigate complex business performance questions.
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Develop time-based analytical calculations for year-to-date performance, cumulative totals, period comparisons, rankings, and business growth measurements.
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Configure cube processing, partitions, aggregations, and storage settings to improve analytical performance and support growing organizational data volumes.
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Implement SSAS security, role management, deployment, backup, monitoring, and maintenance procedures to ensure reliable analytical services.
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Integrate multidimensional analytical models with reporting and visualization platforms, including Excel, SSRS, and supported Power BI environments.
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Evaluate multidimensional analysis solutions and apply optimization, governance, and documentation practices to strengthen enterprise decision support.
Comprehensive Course Outline
Module 1: Introduction to SQL Server Analysis Services and Multidimensional Analytics
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Examine the purpose, architecture, components, and enterprise applications of SQL Server Analysis Services in modern business intelligence environments.
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Understand Online Analytical Processing, multidimensional analysis, analytical databases, and the differences between OLTP and OLAP systems.
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Explore data warehouse architecture, dimensional modeling principles, and the role of fact tables and dimension tables in analytical solutions.
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Compare multidimensional and tabular Analysis Services models, identifying their respective capabilities, use cases, and implementation considerations.
Module 2: SSAS Development Environment and Data Source Configuration
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Set up and explore the SSAS development environment using supported SQL Server Data Tools, project templates, and Analysis Services extensions.
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Create Analysis Services projects and configure project properties, deployment settings, and development structures for multidimensional solutions.
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Establish data sources and data source views to connect analytical models to SQL Server databases and supported enterprise data repositories.
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Examine source table relationships, keys, metadata, and schema requirements for preparing reliable multidimensional analytical structures.
Module 3: Dimension Design and Hierarchy Development
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Develop dimensions from warehouse tables and configure dimension attributes, keys, names, and attribute properties for analytical reporting.
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Create natural and user-defined hierarchies that enable users to navigate business information across organizational and reporting levels.
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Configure attribute relationships, dimension properties, and relationship structures to improve model organization and analytical query performance.
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Implement common business dimensions such as time, geography, customer, product, department, supplier, and organizational unit.
Module 4: Cube Development and Measure Group Configuration
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Create multidimensional cubes by selecting appropriate fact tables, dimensions, measures, and measure groups based on business reporting requirements.
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Define measures and configure aggregation functions such as sum, count, distinct count, minimum, maximum, and other supported calculations.
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Establish dimension usage relationships, including regular, referenced, many-to-many, and fact relationships where appropriate.
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Design cube structures for financial analysis, sales performance, inventory management, procurement reporting, and organizational performance monitoring.
Module 5: Advanced MDX Queries and Analytical Calculations
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Understand MDX syntax, cube coordinates, tuples, sets, members, and the multidimensional query structure used to retrieve analytical information.
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Develop MDX queries using SELECT, FROM, WHERE, and related clauses to explore measures and dimensions from different analytical perspectives.
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Create calculated members, named sets, and scoped calculations to introduce business-specific analytical logic into multidimensional models.
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Apply MDX functions for filtering, ranking, navigation, aggregation, and comparison to answer complex business reporting questions.
Module 6: Time Intelligence and Advanced Multidimensional Analysis
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Develop time-based calculations for year-to-date, quarter-to-date, and month-to-date reporting using appropriate time dimensions and MDX functions.
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Implement period comparisons, previous-period analysis, cumulative totals, moving calculations, and growth measurements for performance monitoring.
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Apply analytical techniques for identifying trends, comparing business units, evaluating product performance, and measuring customer behavior.
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Build multidimensional analysis scenarios for budgeting, forecasting, profitability assessment, operational efficiency, and strategic performance evaluation.
Module 7: Cube Processing, Partitions and Aggregation Optimization
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Understand SSAS processing operations, including dimension processing, measure group processing, cube processing, and incremental data updates.
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Design partitions to organize large measure groups, improve processing efficiency, and support manageable analytical data refresh operations.
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Configure aggregation designs and storage modes, including MOLAP, ROLAP, and HOLAP, according to analytical workload requirements.
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Monitor processing performance, identify bottlenecks, and optimize cube structures to improve query response times and resource utilization.
Module 8: SSAS Security, Administration and Deployment
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Configure database roles, dimension security, cell security, and permissions to control access to sensitive analytical information.
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Manage SSAS databases, deployment configurations, processing schedules, backup procedures, and recovery operations.
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Monitor server activity, troubleshoot processing and query errors, and maintain reliable Analysis Services environments.
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Apply documentation, change management, governance, and access control practices to support secure and sustainable enterprise analytics.
Module 9: SSAS Integration with Reporting and Modern Business Intelligence Platforms
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Connect multidimensional SSAS models to Microsoft Excel and other supported analytical clients for interactive reporting and data exploration.
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Integrate analytical cubes with SQL Server Reporting Services and supported Power BI environments for enterprise reporting and visualization.
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Examine how multidimensional models support centralized business measures, consistent reporting definitions, and reusable analytical structures.
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Explore hybrid analytical architectures, cloud data services, modern semantic models, and the evolving role of SSAS in Microsoft business intelligence ecosystems.
Module 10: Enterprise Multidimensional Analytics Implementation and Practical Projects
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Translate business requirements into multidimensional model specifications, identifying appropriate measures, dimensions, hierarchies, and analytical calculations.
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Develop an end-to-end SSAS multidimensional cube using warehouse data and configure its dimensions, measure groups, and relationships.
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Implement MDX queries and calculations to produce business reports covering financial results, sales trends, operational indicators, and performance comparisons.
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Evaluate cube accuracy, processing efficiency, query performance, security, and usability while presenting a practical analytical solution for management decision support.
Training Approach
This course will be delivered by our skilled trainers who have vast knowledge and experience as expert professionals in the fields. The course is taught in English and through a mix of theory, practical activities, group discussion and case studies. Course manuals and additional training materials will be provided to the participants upon completion of the training.
Tailor-Made Course
This course can also be tailor-made to meet organization requirement. For further inquiries, please contact us on: Email: training@upskilldevelopment.com Tel: +254 721 331 808
Training Venue
The training will be held at our Upskill Training Centre. We also offer training for a group (at a discount of 10% to 50%) at requested location all over the world. The Onsite course fee covers the course tuition, training materials, two break refreshments, buffet lunch, airport transfers, Upskill gift package, and guided tour.
Visa application, travel expenses, dinners, accommodation, insurance, and other personal expenses are catered by the participant
Certification
Participants will be issued with Upskill certificate upon completion of this course.
Airport Pickup and Accommodation
Airport pickup and accommodation is arranged upon request. For booking contact our Training Coordinator through Email: training@upskilldevelopment.com, +254 721 331 808
Terms of Payment:
Unless otherwise agreed between the two parties’ payment of the course fee should be done 3 working days before commencement of the training so as to enable us to prepare better.
