Big data has quickly become a critical asset for businesses of all sizes, and in all industries.
However, data alone does not automatically create value. It takes a strong business intelligence developer to be able to manipulate and analyze data to help business leaders make informed decisions.
The US Bureau of Labor Statistics predicts that the demand for Business Intelligence Developers will increase by 22% by 2030. As companies seek to make use of their data, the market for advanced business intelligence skills will become even more competitive than it is today.
This is great news for business intelligence developers, who can take advantage of the market and command a higher salary; but first, you must show your expertise. Prepare for your next interview to put yourself in a position to negotiate your salary and take your pick of the opportunities out there.
Business Intelligence Job Interview: Top Questions and Answers
Here are seven common business intelligence interview questions — and some good answers you can use — to help you stand out in the job market.
1. Which BI tools do you have experience using?
There are a range of BI tools on the market, and each company with which you interview may use something different. According to experts, the most common BI tools are Microsoft Power BI, Tableau, Qlik, SAS BI, and ThoughtSpot.
Be honest about the BI tools that you are well-versed in using! There’s no wrong answer here. Most interviewers ask this question to understand what resources and training you will need to be successful. If you have experience with a few different BI tools, mention how they overlap and work together so that your hiring team can see that you are a quick learner. This also shows that you understand the intricacies of each platform, its role and limitations.
2. What is the biggest non-technical challenge you faced?
Many interviewers will be able to see from your resume, portfolio, or skills assessment that you have the technical expertise to work as a business intelligence developer. However, they’ll also want to know about your soft skills. This question aims to understand how you think through problems, work creatively, and communicate.
Business intelligence isn’t just about diving into the data. These experts must also be able to explain their analyses and provide potential solutions to business problems. As such, use your answer to show how you break down a complex data set into manageable business insights. How do you translate your technical work for a nontechnical audience?
3. What steps would you take to implement BI analytics for our company from the ground up?
Despite the growth of Big Data, many companies still don’t have a robust BI analytics function built into their operations. They may be hiring you to do just that. How would you approach this task?
Do your research before the interview to understand the company and anticipate its business needs. A good answer would include steps such as building analytical data storage, creating a schema for storing existing data and updating this storage regularly, establishing BI tools and reports, and providing reports to leadership to meet changing business needs. You could talk about the tools you would use, how you would secure data storage, and even some key reports you would run to benefit the business.
4. What’s the difference between OLTP and OLAP?
If you do get asked a technical question, it may be one such as this.
OLTP stands for online transactional processing. This type of processing is used for customer-facing business applications. OLTP enables the real-time execution of large numbers of database transactions by large numbers of Internet users.
OLAP stands for online analytical processing. An internal function, OLAP is used to steer the company. “OLAP is ideal for data mining, business intelligence and complex analytical calculations, as well as business reporting functions like financial analysis, budgeting and sales forecasting,” wrote IBM.
OLAP and OLTP are both necessary parts of business intelligence, and knowing when and how to use each option can showcase your expertise.
5. Why should you normalize your data?
Good business intelligence experts know that there are many benefits to data normalization. The more benefits you can name, the better!
Data normalization removes duplication that can skew your analysis and take up too much space in your data storage. It allows for finer “transaction granularity” — meaning that data could be modified separately in its own transaction without impacting its foreign key relationships.
Normalization also helps streamline the analysis process. Once data is normalized, BI developers can start to use data without the need to modify as you go. This reduces errors and inconsistencies, as well as increases productivity.
6. What’s the difference between a snowflake and star schema?
A star schema provides a more efficient way to organize data in a data warehouse. A snowflake schema is a variation of a star schema. Snowflake schemas provide more efficiency in processing data.
Here’s a quick cheat sheet to use when preparing to answer this question, courtesy of Educba:
7. What BI projects have you worked on?
Finally, expect to talk about your experience. According to Indeed, most employers expect business intelligence professionals to have a degree in either information technology, business intelligence, computer science, mathematics or software development. Talk about your academic experience in addition to your job experience to show you have a solid foundation of skills that can adapt in this competitive field.
When you talk about your past BI projects, emphasize skills that will translate to future projects for your prospective employer. Talk about your work in data collection, analysis, visualization, architecture; business strategy; risk mitigation; or even with specialized teams and projects, like accounting or project management. This will show you have the right attitude to work with a variety of different teams.