bi technical interview questions

• What is your preferred visualization tool to use for presentations? …
• What are some unique business insights you’ve drawn from previous projects? …
• Why do you think BI is important for companies today? …
• How would you use incomplete data sets in your visualizations?

10+ Business Intelligence Interview Questions!

The Skills You Need for a Business Intelligence Job

“Business intelligence” is so broad that it touches on just about every company, many departments within those companies, and employees with different job titles and a vast assortment of skills. BI refers to the processes, architectures and technologies that enable raw data to be transformed into actionable insights so that business leaders can make informed decisions. However, the processes and technologies organizations employ vary from firm to firm.

Tim Herbert, executive vice president for research and market intelligence at CompTIA, points to three components to BI job duties: data, analytics and reporting. “The data component typically requires a BI professional to understand, manage and sometimes create the processes for collecting, storing, structuring, cleaning and anything else to make data usable for analytics,” Herbert explains. “The analytics component may entail trending analysis of data over time, developing summary metrics, applying descriptive statistics and related [steps].

“Lastly, the reporting function entails equipping company executives and business unit staff with actionable data to make smart business decisions. Over the years, this has meant moving away from long, static reports to shorter data visualizations, online dashboards or other real-time data reporting applications.”

Success in business intelligence and related fields requires myriad technology skills, such as computer programming and database familiarity, as well as soft skills, such as interpersonal skills. The software, hardware and services needed for BI success change over time. So, professionals seeking positions related to BI should be versed in state-of-the-art as well as emerging BI technologies, tools and practices.

Good analytical skills are necessary for deciphering large amounts of data and transforming it into actionable information to make the right decisions to boost company profits. Gathering data and mastering statistical and analytical tools for data extraction and interpretation are also essential and require professionals knowledgeable in database management, data queries, coding data, drawing inferences, applying scientific methods to gathering data, quantitative analysis, SQL programming, establishing benchmarks, identifying and measuring correlations, classifying data and strategic planning.

BI professionals must also be adept at describing the data, explaining their analysis and offering potential solutions. Communicating clearly and effectively is important because they need to be able to explain complex technical information to non-BI professionals. BI professionals may also have to persuade others to adopt ideas, manage projects or spearhead brainstorming sessions. Their skill list might include technical writing, pitching proposals, making presentations, facilitating group discussions and teamwork, and conveying complex information in clear terms.

Tips to Prepare for the Interview Process

When youre invited to interview for a BI job, whats the best way to get ready? Do some research and strategizing ahead of time so that you can comfortably answer general questions about the BI field and your background. Research the company online and request a description of the potential job, the organization or client for which youll be working. Review key BI skills that the company might require and spend some time thinking about how yours match up. Look for clues about the companys BI strategy.

Youll undoubtedly learn more about the organization and its needs as you interview with different people at the company, but here are key questions to think about before your interviews.

“Business intelligence” is an umbrella term and refers to roles that are continuously evolving, so interviewees should be prepared to offer their definition of the term to show that they understand the field, its importance and how it is changing.

Be familiar with textbook definitions for BI, but consider adding your own twist, potentially by discussing your experience in applying BI processes and tools.

Be aware of key elements of BI, including query generation, data mining, data modeling (including fact tables) and analysis, creation of dashboards and visualization charts, and production of analytics reports. Make sure you are up-to-speed on recent and emerging developments in the field.

Consider brushing up your BI vocabulary. The interviewer might use terms such as “process intelligence” or “business intelligence architecture.”

It might also be worth distinguishing between business intelligence and data science, a different but closely related data analytics field. According to Dataversity: “While BI helps interpret past data, data science can analyze the past data (trends or patterns) to make future predictions. BI is mainly used for reporting or descriptive analytics; whereas data science is more used for predictive analytics or prescriptive analytics.” Knowing both terms might be helpful because some BI jobs may incorporate elements of data science, or the BI professional might work closely with the data scientist.

When you walk in for your interview, you need to be prepared to speak at length about business intelligence. This extends to what BI is important, as you need to be able to contextualize your job in the bigger picture of the business.

Business intelligence is important because it can help improve all parts of a company through data. By improving access to the organizations data, BI can translate data into valuable insights into business processes. These insights can help leaders make informed decisions that lead to better efficiency and productivity, which fuel revenue and growth.

Business intelligence tools can help organizations:

Improve decision-making with data-driven insights

Identify market trends

Identify weak points in their business operations

Increase efficiency of operations and internal processes

Gain advantages over market competitors

When preparing for this question, reading about current events and emerging trends in BI technology can be a good way to help form a strong answer.

Companies are looking for individuals who are committed to a data-oriented culture and enthusiasm over BIs potential. You might describe BIs benefits such as improving decision-making, operational efficiencies, and top- and bottom-line growth as well as providing competitive advantages. A follow-up question might be how to apply BIs benefits to the company for which you are interviewing.

Another way interviewees might show enthusiasm for the field is to discuss how it is evolving, with BI software becoming more collaborative, proactive, insightful and better equipped to handle big data as well as fostering more automation and greater integration with other key platforms. Show an interest in where an interviewer stands regarding recent trends in mobile business intelligence or AI adoption, for example.

Citing trends can also make a positive impression with the interviewer. A few current BI trends include:

BI teams are becoming more diversified, including business-side users among the BI developers, architects, analysts and data scientists.

Many organizations are now starting to replace Waterfall development methods with Agile development. Agile breaks up BI development projects — which are delivered to BI analysts to use — into smaller pieces. These pieces are delivered iteratively. Agile allows businesses to implement new functionalities faster and make refinements or modifications in response to business needs (which are subject to change).

Use this and other questions regarding your background to discuss BI-related projects youve been involved in. Discuss current or recent BI roles youve had or would like to have as well as what youve learned or would like to learn. Mention degrees, internships, bootcamps and certification programs that are relevant to the job.

Advanced degrees are not typically required to be considered for full-time BI analyst positions; BI analysts do need undergraduate degrees, however. Common areas of study for BI analysts include business administration, IT, data science, engineering and other related fields.

Make sure to emphasize any courses that offered relevant skills and experience, such as:

Data collection, analysis, visualization, architecture

Business strategy

Risk mitigation

Accounting software

When giving an overview of your background, avoid getting bogged down with extraneous details. You might focus on the present and future — and briefly touch on the distant past.

For technical interviews, candidates will likely be asked specifics about the tools they use. The required tools are typically outlined in the job description. According to Simplilearn, the top 5 BI tools are:

Other tools include:

Interviewers will ask this question to understand the time and resources needed for a candidate to be productive. During the interview, be honest about which tools you have or havent used. If you do have experience with the tool(s) in question, share your level of expertise. If you dont have any experience, ask the interviewer if this itself is a deal breaker. Make sure to include any other business intelligence tools that you do have experience with, and mention any areas of overlap between these tools, which can flatten the learning curve. If you have solid experience with multiple other business intelligence tools and mention that you are a quick learner, then your interviewer will have more confidence in your ability to bridge the learning gap and become a productive member of their team.

While interviewing for positions, its important for you to communicate your desire to learn and improve your business intelligence analysis skills. The last thing an interviewer wants to see is a potential employee thats complacent with their skill set.

To answer this question, pick two or three and be prepared to explain how it fits into your interest and goals. Potential answers might include dashboard design, database management, advanced statistics and analytics, and Python or other programming languages.

This question seems intuitive, but a novice might not be able to answer this question at the top of their heads. A BI dashboard displays on a single screen the status of business analytics metrics, KPIs and important data points for an organization, department, team or process.

When asked this question, explain clearly about a BI challenge with which you are familiar so that potential employers can gain insight into the thought processes that you might put into identifying problems and contributing factors, proposing alternatives and estimating costs to address them. Employers might be wary of candidates who cannot come up with any challenges they have faced.

Now for some hard questions. When asked to provide some of the toughest questions that could be lobbed at a candidate during an interview for a BI role, Paul Farnsworth, chief technology officer at DHI Group, Inc., parent company of Dice, offered the following:

Explain the difference between Kimball, Inmon and Data Vault data warehouse designs, and give examples of when you would use each.

Explain the following three things: common table expressions (CTEs) vs. temp table vs. physical staging table. Give examples of when you would use each.

Databases have come a long way with features for analytics-focused databases. How do you tune for analytic performance in modern database solutions?

Explain the benefits of cloud data warehouses (Redshift, Snowflake, BigQuery, etc.) vs. on-premises solutions.

Explain the following and what role each one serves in the data warehouse ecosystem:

• enterprise data warehouse
• data mart
• operational data store
• data lake

Explain some of the different types of slowly changing dimensions.

BI professionals must also be adept at describing the data, explaining their analyses and providing potential solutions. They may also have to persuade others to adopt ideas, manage projects or spearhead brainstorming sessions. Their skill list might include technical writing, pitching proposals, making presentations, facilitating group discussions and teamwork, and conveying complex information in clear terms.

Whether you are answering a technical or non-technical question, always try to distinguish yourself from others and explain why the company should hire you — without being conceited, insincere or dishonest.

Analyst vs Engineer: What’s the Difference?

In simple terms, business intelligence, or BI, is the practice of applying insights from data to the problem of running an enterprise business. This field is split between two common careers (BI analysts and BI engineers).

While there is some overlap between the two roles, a BI engineer mainly constructs and maintains the data pipeline that a BI analyst uses to deliver insights to their employer. Therefore, BI engineers have a more technical role than BI analyst and require specialization in data storage and ETL tools.

As a result, there is some divergence in the questions asked of business intelligence analysts vs. engineers. SQL questions are the most frequently asked topic in both business intelligence analysts and engineer interviews.

However, analysts can expect more business sense and business case study questions, while engineers tend to receive more database design and Python questions.

Business intelligence interviews at tech, financial firms and other large companies follow a standardized process. The process typically progresses like this:

Phone Screen The first step is a call with a recruiter or hiring manager. This call is used to see if your career goals and experience align with the role, if you have the right skills, and to gauge your interest in the position. Be prepared for questions about your past experience, BI projects you have worked on, and business problems you have been asked to solve.

Technical Interview The technical screen is used to assess your technical skills. These screens focus on SQL and statistics (for both analysts and engineers), while engineering interviews also include 1-2 questions on Python. Depending on the company, you may be asked to whiteboard code or write code using a shared editor.

On-Site Interviews On-site interviews vary by company, but most include 3-5 sessions that focus on SQL, statistics, Python, business sense and culture fit. Amazon business intelligence interviews, for example, include 5 rounds:

SQL and basic statistics

SQL and scenario-driven behavioral questions

Business case study interview

Behavioral interview focused on leadership

Statistics and product sense interview

Check out our Amazon Business Intelligence Engineer Interview video:

Toptal sourced essential questions that the best Business Intelligence developers and engineers can answer. Driven from our community, we encourage experts to submit questions and offer feedback.

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What is a data cube (or “OLAP cube”)?

A data cube describes the BI data structure in memory before it is shipped to a BI UI tool to be displayed to the user. It is a multi-dimensional data representation made for better visualization, data slicing, and drill-down techniques. The UI usually does not display a literal cube, but generally 2D slices of it for better human readability:

A data cube is usually based on a single denormalized fact table and some number of dimension tables representing data cube dimensions. The star and snowflake schemas were specifically designed to aid in building data cube structures in memory.

An example schema might consist of:

Time buckets—time dimension table

Customers—customer dimension table

Products—product dimension table

Sales amount (units sold)—fact table

The data cube structure for this schema can be thought of like this:

Describe fact and dimension tables.

A fact table contains dimension keys and numerical values for some measures. Each dimension key represents a dimension that measures are for. Measures can be aggregated across dimensions to build a drillable data cube.

Dimension tables are dictionary tables used to display dimension labels and information on BI visual interfaces.

What are the steps to implement company BI analytics from the ground up?

Build company analytical data storage (data warehouses, data marts).

Devise an analytical data storage schema based on both actual company data and BI demands.

Initially, populate analytical data storage with existing company data, and then update it regularly.

Set up BI tools on top of analytical data storage.

Develop BI reports.

Maintain and modify BI reports according to changing needs.

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Name some benefits of data normalization.

The candidate should name at least two benefits from those listed below. It can be in their own words, as long as it’s close in meaning. The more benefits they can name, the better.

Data normalization:

Removes data duplication.

Allows finer transaction granularity. Each referenced table data could be changed independently in its own transaction without affecting its foreign key relationships.

Enables clearer referential integrity. The smaller entities produced by normalization allow modeling business objects and their relations as close to the real world as is possible.

Allows incremental schema changes. Adding or deleting columns in one table does not affect the structure of referenced tables.

What is a data mart? When is it appropriate to use data marts instead of a single data warehouse?

A data mart stores a subset of company data that focuses on a specific department, activity type, or set of subproblems.

Separating data into data marts allows for better performance and separation of tasks for BI analysts and business users.

This strategy is a matter of design and operational convenience. While there is no definitive answer on when to use it or not, it’s usually considered appropriate to build a data mart when a company runs different lines of businesses that are very much independent in terms of their underlying data and reporting needs.

For example, if the same company is building trucks and running an online game application, it likely makes sense to handle these sub-concerns in separate data marts.

What are the star and snowflake schemas?

The star schema consists of dimension and fact tables. Each dimension table represents a “metric” that can be used in BI reporting. A fact table references dimension tables for each corresponding metric the fact table covers.

The snowflake schema is an extension of the star schema in such a way that dimension tables could be further normalized and split into main and secondary dictionary tables.

Define OLTP and OLAP. What is the difference? What are their purposes?

OLTP stands for “online transactional processing.” It is used for company business applications. They are most often customer- (i.e., people- or business-) facing.

OLAP stands for “online analytical processing.” It is used for a company’s internal analysis by department leads and company top management to steer the company.

Which BI tools have you used, and what are their good and bad sides?

There are numerous BI tools on the market, but among the best-known are:

Oracle Business Intelligence Enterprise Edition (OBIEE)

IBM Cognos Analytics

MicroStrategy

The SAS product line

SAP BusinessObjects

Tableau

Microsoft Power BI

Oracle Hyperion

QlikView

This type of free-form question isn’t about the candidate providing a correct answer, per se. It’s more about sparking a discussion so interviewers can get a sense of the depth of the candidate’s expertise, and where that overlaps with the company’s current needs.

What is the purpose of BI?

BI provides quick and simple methods to visualize company metrics, generate reports, and analyze data.

These methods, in turn, help top management to:

Analyze existing trends.

Lay out company development plans.

Ensure such plans are executed as scheduled.

Detect anomalies and problems.

Apply corrective actions.

Name some benefits of data denormalization.

The candidate should name at least two benefits from those listed below. It can be in their own words, as long as it’s close in meaning. The more benefits they can name, the better.

Data denormalization provides:

Simpler initial data schema design.

Better data write/read performance.

Direct applicability in data warehouses. Fact and dimension tables in data warehouses are usually designed without regard to data normalization to ensure fast and straightforward data retrieval.

Precomputation and query performance improvements for data cube BI slice-and-dice and drill-down analysis.

What are the primary responsibilities of a BI developer?

BI developers are generally expected to:

Analyze company business processes and data.

Standardize company data terminology.

Gather reporting requirements.

Match the above requirements against existing data.

Build BI reports.

Analyze the fleet of existing reports for further standardization purposes.

This question can be useful as an opening one—not just to help filter undesirable candidates and put more qualified candidates at ease but also to provide an opportunity to discuss any nonstandard responsibilities that may be involved in the particular job at hand.

There is more to interviewing than tricky technical questions, so these are intended merely as a guide. Not every “A” candidate worth hiring will be able to answer them all, nor does answering them all guarantee an “A” candidate. At the end of the day, hiring remains an art, a science — and a lot of work.

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Submitted questions and answers are subject to review and editing, and may or may not be selected for posting, at the sole discretion of Toptal, LLC.

Alejandro got his bachelors degree in software engineering in 2005 and has since been working for software companies of all sizes from all around the globe as a freelancer. Currently, he enjoys working as a full-stack architect in JavaScript projects, where his experience and his deep understanding of architecture and theory are most impactful.

Tim is a software architect and developer with a proven ability to develop efficient, scalable, and fault-tolerant server solutions for complex problems. He has excellent analytic abilities and extensive experience with big data real-time processing, server solutions, and web services.

Shanti is a top-notch, hands-on technical leader. He has delivered multiple video game titles and apps for server, desktop, web, and mobile. He is results-oriented and will contribute whatever the team needs, from high quality code to inspired leadership.

FAQ

How do I prepare for a BI interview?

1. What is your definition of “business intelligence?” …
2. Why is business intelligence important? …
3. What interests you most about the BI field? …
4. What can you tell me about yourself and the BI projects you have worked on? …
5. Which BI tools do you have experience using?

What is a BI interview?

What are the BI roles and responsibilities?

• Data Analysis.
• Problem-solving.
• Specific industry knowledge.
• Communication skills.
• Data visualization and interpretation.
• Advanced vision and attention to detail.
• Statistical analysis.
• Technical notion.