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Modern business operations heavily rely on the vast amounts of data generated through the customers and users. Converting data into meaningful information is essential to understand and analyze the business insight that will help drive the company towards profitable actions. It is where business intelligence comes into effect. Business intelligence helps the users in decision-making to run the business efficiently. According to reports, the business intelligence market is expected to grow from US$23.1 billion in 2020 to US$33.3 billion in 2025, at a CAGR of 7.6%, which proves that the industry is growing and there are several aspiring professionals ready to choose this as a career. Therefore, this article presents the top business intelligence interview questions that are trending among industry hiring experts.
The term business intelligence refers to a collective meaning, including technologies, tools, applications, practices for data collection, and providing those data to the BI users, that will eventually help them run the business. In short, BI is used for reporting the specified data of any business for the growth of the organization.
BI can be implemented in three steps. Firstly, extracting the raw data from the corporate database. And then, the data will be cleaned to put in the data storage by linking the table and forming the data cubes. Lastly, using the BI systems, the analysts can extract business insights, analyze those clean datasets, and predict business decisions.
Data warehousing is the repository system used to analyze and report data from various heterogeneous sources and forms. The data is gathered from various oracle databases, SQL servers, and Postgres, or a simple excel sheet. The warehouse uses one central mechanism called the repository, through which the analysts can fetch all historical reports associated with the data.
Some popular BI tools used by business intelligence analysts are Microsoft BI, Cognos, MicroStrategy, Tableau, SAS, and Hyperion.
A data cube describes the BI data structure in memory before it is shipped to a BI user-interface tool to be displayed to a user. It is a multi-dimensional data representation made for better visualization, data slicing, and drill-down technologies. The UI does not always display a literal cube, instead, it presents 2D slices of it for better readability.
OLTP or online transaction processing systems are the vast collection of small data transactions like insert, delete, and update. these are optional databases that produce quick processing of a query. It also determines the integrity and consistency of data. It counts the number of transactions per second that helps in measuring the efficiency of an OLTP system.
Data normalization removes data duplication. It allows finer transaction granularity. It also enables clearer referential integrity and allows incremental schema changes.
BI systems are mostly expensive, so using them for small and medium-scale enterprises might exceed their budget expenses. Also, implementing BI systems for a data warehouse is complicated, hence, it is also a major drawback.
BI developers are generally expected to analyze company business processes and data. They standardize company data terminology and gather reporting requirements. Also, they create BI reports and analyze the fleet of existing reports for further standardization purposes.
Aggregates are a form of data that are found in the aggregate table. To calculate these aggregates, various aggregate functions such as min, max, and average count are used.
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