Capgemini SSAS Technical Interview Questions and Answers
When it comes to business intelligence and data analytics roles at Capgemini, SQL Server Analysis Services (SSAS) often becomes a key area of technical evaluation. SSAS is widely used in enterprise-level projects for data modeling, OLAP (Online Analytical Processing), and building analytical solutions that power decision-making.
To help you prepare, I’ve compiled a list of commonly asked SSAS technical interview questions with detailed answers.
1. Basic SSAS Questions
Q1. What is SSAS, and why is it used?
SSAS (SQL Server Analysis Services) is a data analysis and business intelligence tool by Microsoft. It allows developers to create OLAP cubes and Tabular models that support fast querying, data aggregation, and reporting. It is mainly used for data warehousing, dashboards, and advanced analytics.
Q2. What are the different types of models available in SSAS?
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Multidimensional Model (OLAP Cube): Traditional cube-based modeling, supports complex hierarchies.
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Tabular Model: Uses relational tables with in-memory storage, more modern and faster for many scenarios.
Q3. What are Dimensions in SSAS?
Dimensions are structures that categorize data in the cube. They define descriptive attributes like Product, Time, Geography, or Customer, which help analyze measures.
Q4. What are Measures in SSAS?
Measures are numerical data values that can be aggregated (like Sales, Profit, Quantity). They are the metrics that business users analyze across dimensions.
Q5. What is a Cube in SSAS?
A Cube is a multidimensional data structure in SSAS that stores pre-aggregated data for fast querying and reporting. It combines dimensions and measures to provide powerful analytics.
2. Intermediate SSAS Questions
Q6. Explain the difference between OLAP and Tabular models in SSAS.
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OLAP (Multidimensional): Uses cubes, supports advanced hierarchies, MDX queries, large data sets.
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Tabular: Uses tables and relationships, supports DAX queries, optimized for in-memory analytics, easier to develop.
Q7. What is a Data Source and Data Source View (DSV) in SSAS?
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Data Source: Defines the connection to the database (SQL Server, Oracle, etc.).
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DSV: A logical view of source tables, relationships, and joins used to design cubes and models.
Q8. What is an SSAS Partition?
A Partition divides a large measure group into smaller, manageable parts. It helps in improving query performance and enables parallel processing.
Q9. What is a Role in SSAS?
Roles are security objects in SSAS that define user permissions such as Read, Write, Process, or Admin access on cubes, dimensions, or models.
Q10. What is Aggregation in SSAS?
Aggregations are pre-calculated summaries of data (like sum of sales by region) that speed up query response times.
3. Advanced SSAS Questions
Q11. What is the difference between MDX and DAX in SSAS?
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MDX (Multidimensional Expressions): Query language for OLAP cubes.
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DAX (Data Analysis Expressions): Used in Tabular models and Power BI for calculations.
Q12. What are Key Performance Indicators (KPIs) in SSAS?
KPIs are business metrics like profit margin or sales growth, defined in SSAS with a goal, actual value, and status indicator (green, yellow, red).
Q13. What is the use of Hierarchies in SSAS?
Hierarchies define levels of data granularity, such as Year → Quarter → Month → Day, making it easier to drill down in reports.
Q14. How does SSAS handle security?
SSAS provides:
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Role-based security (Read, Write, Admin).
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Dimension security (restrict access to specific dimension members).
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Cell-level security (restrict access to certain measure values).
Q15. What are Calculated Members in SSAS?
Calculated Members are custom measures or dimensions defined using MDX/DAX expressions, for example:
Profit = Sales – Cost
4. Real-Time Scenario-Based Questions
Q16. Suppose your SSAS cube query performance is very slow. How would you optimize it?
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Create proper aggregations.
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Use partitions to divide large data sets.
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Optimize data source queries.
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Ensure indexes are created in the underlying database.
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Consider switching to Tabular models if in-memory analytics is better suited.
Q17. How do you implement Row-Level Security in SSAS?
By defining roles with dimension filters (like restricting users to see only data for their region).
Q18. If the client asks for real-time analytics in SSAS, how would you achieve it?
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Use DirectQuery mode in Tabular models to query live data from SQL Server.
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Or schedule frequent cube processing to keep data updated.
Q19. How do you deploy an SSAS project to production?
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Use SQL Server Data Tools (SSDT) to design the model.
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Deploy via SQL Server Management Studio (SSMS) or Visual Studio Deployment Wizard.
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Validate security roles and process the cube.
Q20. How do you monitor and troubleshoot SSAS performance?
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Use SQL Server Profiler for query tracing.
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Monitor via Performance Monitor (PerfMon) counters.
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Use Dynamic Management Views (DMVs) to analyze performance and memory usage.
Final Thoughts
Capgemini’s technical interviews for SSAS roles focus on both conceptual understanding and real-time implementation skills. Candidates should be strong in:
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OLAP and Tabular modeling
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MDX/DAX queries
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Performance tuning strategies
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Security (roles, row-level security)
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Deployment and troubleshooting
A well-prepared candidate who can explain real-world problem-solving with SSAS will have a strong edge in the interview.
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