MS BI technology interview questions provides you guidance that helps answer them successfully to demonstrate your understanding of MS BI technologies and practices.

Microsoft Business Intelligence is an invaluable tool that enables organizations to make data-driven decisions by providing insights and visualizations from their data.

MS BI comprises numerous components including SQL Server Reporting Services, Analysis Services and the Data Warehouse.

Let’s dive in! In our inaugural post, we’ll introduce some key components and features of MS BI technology – as well as their roles within MS BI landscape – with their functions described.

Stay tuned for future interviews focused on MS BI tech!

1.What does BI stand for?

Business Intelligence

2.Mention some other BI tools in the market besides Microsoft Business Intelligence (MSBI)?

ABI N Issue, Informatica, Spotfire, Tableau

 3.How do BI tools add value to businesses?

By providing efficient solutions for business intelligence and data mining, they enable businesses to make better decisions.

4.Can you explain the scenario where A B C, a pharmaceutical company, uses different systems to track sales at its retail outlets?

A B C’s retail outlet one uses an Excel sheet to track daily sales, while A B C’s retail outlet two uses a full-fledged SQL server solution setup.

5.What is the objective of ABC in this scenario?

To understand how well it is doing in terms of sales and customer buying behavior.

6.How does ABC plan to achieve this objective?

By collecting data from all its retail outlets and consolidating it into one common format.

7.Tell about some possible data sources that ABC’s retail outlets use to track sales?

Excel sheets, SQL servers, Oracle databases, flat file formats, DBS2 databases

8.Why is it important for ABC to perform meaningful analytics on this consolidated data?

To gain a comprehensive understanding of its sales performance.

9.What is the goal of consolidating and consolidating data from various retail outlets?

To simplify holistic analytics by converting all disparate data sources into one common destination format.

10.List out the benefits of this approach?

It does not require people with different skill sets or technologies to perform analytics.

However, maintaining different systems that are not visible is a cost from the company’s point of view.

11.Define Management Studio?

A Management Studio is a database management system that allows users to create and manage databases.

It uses a script to display data as a table, which is stored as a file on the hard disk.

12.Give the definition of backup and restore?

A Backup and restore are part of a Disaster Recovery Measure (DRM) that involves saving data files and copying them back on a different machine.

This allows users to move their databases from one server to another, implementing out-of-reach measures.

13.How do I back up a database in Management Studio?

A To back up a database in Management Studio, you can right-click on it and go to tasks. You can generate a dot B file, which stores the destination as a dot B file.

14.What are the steps to restore a database in Management Studio?

To restore a database in Management Studio, you can search for the file, click on the device, and click on the ellipse sign.

You can choose the backup file you want to restore and navigate through the options.

15.Define SQL Server data warehouse?

SQL Server data warehouse is a database that stores aggregated data and is used for reporting and analytics.

16.What is SQL Server Analysis Services?

SQL Server Analysis Services is a component of SQL Server that helps build a cube, which is a data structure used for data warehousing and analytics.

17.Elaborate is SSA?

SSA (Selective Suppression Analysis) is an optional component that allows for faster generation of aggregated data by storing aggregates in a queue.

18.What is MSBI ETL and reporting solution?

MSBI ETL (Extract, Transform, Load) and reporting solution is a software suite used for data integration and reporting.

19.Define a data warehouse?

A data warehouse is a database that stores aggregated data and is used for reporting and analytics.

20.Is all data warehouses an SQL Server data warehouse?

No, all data warehouses are not SQL Server data warehouses. However, all SQL Server data warehouses are databases.

21.Point out the difference between SSA and a queue solution?

SSA is an optional component, and reports can be generated using the database as well.

The queue is the optional component from a performance standpoint, and for better performance, a queue solution is typically implemented on top of the MSBI ETL and reporting solution.

22.What is the purpose of MSBI ETL and reporting solution?

The purpose of MSBI ETL (Extract, Transform, Load) and reporting solution is to integrate data from multiple sources, transform it into a format suitable for analysis, and load it into a data warehouse.

It is used for data integration and reporting.

23.Give a details explanationof normalization in online transactional processing (OLTP) systems?

Normalization is a process of breaking down a large table into smaller tables to enable faster inserts, updates, and deletes in an OLTP system.

24.Why is normalization important for operational systems?

Normalization is important for operational systems because it enables faster inserts, updates, and deletes, which is essential for a robust transactional processing system.

25.How does normalization increase the number of joins involved in a query?

Normalization increases the number of joins involved in a query because it breaks down a large table into smaller tables, resulting in more tables that need to be joined.

26.What is the impact of normalization on select statements?

Normalization reduces the speed of select statements because it increases the number of joins involved in the query, which can take more time to execute.

27.Mention the main focus of a data warehouse?

The main focus of a data warehouse is on analytics rather than supporting an operational OLTP system.

 28.Why is a data warehouse denormalized?

A data warehouse is denormalized to allow for faster inserts, updates, and deletes, which is essential for analytics.

 29.Why is a data warehouse recommended for reporting purposes?

A data warehouse is recommended for reporting purposes because it is designed to handle complex select statements and maintain a denormalized structure, allowing for faster inserts, updates, and deletes.

 30.What is a data warehouse?

A data warehouse is a system designed to store historical data, spanning decades and allowing for trend analysis and analytics.

31.What does a data warehouse not do?

A data warehouse does not insert, update or delete data, but inserts do occur due to new data being added.

32.Why is inserting data slower in a data warehouse compared to an operation system?

Inserting data in a data warehouse is slower than in an operation system because inserts happen all the time in the latter.

33.What should the report generated by a data warehouse be like?

The report should be fast, denormalized, and have data across the past day and years.

 34.Why is a denormalized database ideal for reporting?

A denormalized database is ideal for reporting because it requires lesser joins and ports run quickly, making select statements run fast.

35.What are the factors that must be identified when building a data warehouse?

When building a data warehouse, companies must first model the data warehouse by identifying packs, dimensions, and relationships between them.

36.Define ETL process?

ETL involves extracting data from the source, performing transformation on it, and loading the data onto a data warehouse or database.

37.List out the difference between classical and non-classical ETL?

In classical ETL, the process involves extracting data from the source, transforming it, and loading the data onto a destination.

In non-classical ETL, the process involves extracting data from the source, performing transformation on it, and loading the data onto a data warehouse or database.

 38.How does historical data in a data warehouse differ from data in a data warehouse?

Historical data in a data warehouse is like an old mine-up data, which means it is stored for a long time and can be used for trend analysis and analytics.

Now its time to give a quick revision with MCQ’s

1.What is the goal of consolidating and consolidating data from various retail outlets?

To simplify holistic analytics by converting all disparate data sources into one common destination format.

Used for detailed analytics on different data sources without maintaining different systems.

To perform detailed analytics on different data sources without converting them into a single destination format.

Used to perform detailed analytics on different data sources without any consideration for data consolidation.

2.What is the process of ETL (Enter-To-Load)?

Extracting data from the source, performing transformations on the data, and loading the data into a common destination, such as a SQL server.

Extracting data from a SQL server, performing transformations on the data, and loading the data into a different SQL server.

Extracting data from different sources, performing transformations, and loading the data into a single SQL server.

Extracting data from a single SQL server, performing transformations, and loading the data into different SQL servers.

3.What is the goal of SSRS (SQL Server Reporting Services)?

To perform detailed analytics on different data sources without consolidating them into a single destination format.

To simplify analytics by providing information for various queries, such as sales trends over the past year across different regions, gender categories, product categories, and brackets.

To perform detailed analytics on different data sources without consolidating them into a common destination format.

To perform detailed analytics on different data sources without any consideration for data consolidation or visualization.

4.What is the process of SSA (Selective Suppression Analysis)?

Extracting data from a SQL server, performing transformations on the data, and loading the data into a different SQL server.

Extracting data from different sources, performing transformations, and loading the data into a SQL server.

Extracting data from a SQL server, performing transformations, and loading the data into a common destination format.

Extracting data from different sources, performing transformations, and loading the data into a common destination format

5.What is a data warehouse?

A system designed to handle complex select statements and maintain a denormalized structure, allowing for faster inserts, updates, and deletes.

specific thing in S Q L Server and all data warehouses are databases.

its  part of a database.

All databases are not data warehouses.

6.What is the purpose of a data warehouse?

Insert data, update or delete data, but inserts do occur due to new data being added. 

provide a management meeting with a report that can tell the story of an organization over the past decade.

Handle complex analytical queries and maintain a normalized structure.

Support an operational OLTP system.

7.What is the ETL process?

Extracting data from an OLTP system for reporting needs.

Extracting data from the source, performing transformation on it, and loading the data onto a data warehouse or database.

Inserting data, updating or deleting data, but inserts do occur due to new data being added.

Normalizing a large table into smaller, smaller tables.

8.What is normalization in databases?

The process of breaking down a large table into smaller, smaller chunks, resulting in faster inserts, updates, and deletes.

Its a process of increasing the number of joins involved in the query, which can take more time to execute.

A process of enabling faster selects.

The process of ensuring that databases are designed to support data operations.

Conclusion:

Microsoft Business Intelligence technology offers businesses many benefits when analyzing, visualizing, and sharing data and insights.

Although implementing MS BI may present certain obstacles for organizations, these hurdles can be overcome through clear business goals definition, creating a data governance strategy implementation process with comprehensive training provision as well as cultivating data-driven decision making by creating a culture around data-driven decision-making as well as continuously optimizing MS BI technologies utilizing this approach to data driven insight gathering and use.

Hope  this Mi bi interview questions and answers gave you great revision.