Essential business intelligence analyst skills

Data does the talking in business, and organizations need someone to compile and present it to help companies make informed decisions. Read on to find out which skills can help business intelligence analysts turn raw data into narratives that drive decision-making and results.

Core business intelligence analyst skills are used to generate financial and market insights by pulling information from data repositories and compiling reports. The purpose is to reveal patterns and trends within an organization’s data sources.

Business intelligence skills may include:

• Data analysis: the ability to analyze large datasets and various sources for actionable conclusions.
• Technical skills: knowledge of how to use tools for database management, data queries and development environments, as well as object-oriented programs and web platform development tools.
• Programming skills: the ability to create scripts and instruction sequences that streamline data location and modification.
• Soft skills: the ability to learn, listen, think critically, pay attention to detail, stay organized and communicate clearly with team members.
• Business acumen: an understanding of how data can lead to sound decision-making, including knowledge of how companies operate, compete and build revenue. 

Technical skills for business intelligence focus on turning raw data into accurate and actionable insights. Here are examples of the technical skills used in this field.

Data visualization provides a view of complex data through visual elements such as infographics, plots, charts, graphs and animations. The goal is to present insights in an easily comprehensible way.

Business intelligence analysts should be able to understand the needs, concerns and questions of their target audience. Plus, they should provide a general overview of data points, so audiences can come to the intended conclusion. For example, data visualization can help audiences compare current performance to goals, benchmarks and other metrics.

Statistical analysis involves gathering, categorizing and analyzing data to determine trends and patterns. It’s often used for forecasting, performing simulations and generating statistical models. There are three types: descriptive (summarizes and visualizes data), inferential (uses sample data to draw conclusions) and associational (examines relationships between variables).

Such analysis requires skills in collecting representative data from reliable sources, cleaning and organizing it to remove errors, and presenting it clearly for interpretation. It also involves using software tools and statistical techniques to analyze datasets, identify patterns and uncover relationships.

In business, database management systems are used to compile, store, protect and access data. The systems can help improve business outcomes and operations via data analytics. Business intelligence analysts should understand how database tools and platforms work, including customer relationship management, accounting, credit card processing and point-of-sale programs.

Business intelligence analysts use a variety of tools to complete day-to-day tasks, including:

• Data mining: using statistics, AI and machine learning to scan large datasets and uncover patterns.
• Spreadsheets: for organizing data.
• Online analytical processing: analyzing data from a variety of angles and business perspectives.
• Reporting tools: for data reporting, organization, filtering and display.
• Data visualization programs: to help convert raw data into clear presentations.

Data analytics uses market trends, customer feedback and financial data to help businesses make informed decisions that lead to growth and profitability. 

To get an idea of how business intelligence analyst skills apply in the real world, let’s say a company is experiencing daily challenges with manual reporting that limit access to up-to-date sales and operations metrics. As a result, the company hits roadblocks in decision-making. By adopting an automated business intelligence platform, the company may cut hundreds of work hours annually and enable teams to quickly review operational, budget and profitability data.

In another example, let’s say a company is struggling with labor-intensive manual marketing performance reports that take several hours each day. After moving to a centralized business intelligence system, the analytics team may reduce daily reporting time and effort while using customer behavior insights to tailor regional campaigns that improve conversion and retention.

Data-driven decision-making can also potentially help strengthen collaboration across teams by giving everyone a shared, objective information base and clearer visibility into one another’s work. When teams from different functions rely on common data and metrics, they coordinate more effectively, reduce conflicts and better align their decisions with organizational goals.

A role in business intelligence typically requires an undergraduate degree such as a Bachelor of Science in Data Science. Those who want to enter this field can also develop skills through apprenticeship opportunities, such as the business intelligence engineering program offered by the U.S. Department of Labor.

Business intelligence analysts can also enhance their skills and network with others in the industry by joining organizations such as the International Institute of Business Analysis. The organization offers webinars on process mapping, AI tools, use of business intelligence for return on investment, and leadership workshops.  

To craft a compelling resumé tailored for business intelligence roles, candidates should first carefully read job descriptions to determine what employers are looking for, including the ability to perform specific responsibilities.

A business intelligence resumé should start with a concise professional summary of two or three sentences that demonstrates the candidate’s years of experience and key achievements. For example, employers may want to see what percentage of revenue growth resulted from previous data-driven recommendations.

The work experience section should highlight key responsibilities in previous roles. This could include developing database systems, conducting market research, compiling performance reports, identifying successful milestones and using metrics to make recommendations.

Candidates may find it helpful to include keywords related to business intelligence analyst skills on their resumé that match those listed in the job description. For example, a job description might include words such as “self-sufficient” or “organized.” If you feel those qualities apply to your work ethic, you should include the terms on your resumé as well.

Preparing for a business intelligence analyst job interview means anticipating what hiring managers may ask and practicing well-structured answers that showcase your business intelligence skills and experience. Interview questions usually cover general background, experience and technical knowledge.

General questions might explore your education, strengths, teamwork style, motivations and long‑term goals. Basic questions may be “Why do you want to work for us?” or “What are your plans for the next five years?”

Candidates might also be asked about their work experience. For example, an interviewer might ask, “What data collection tools are you experienced with?” or “Tell me about your experience presenting data.”

Hiring managers may also ask more in-depth technical questions to gauge candidates’ business intelligence analyst skills involving SQL statements, decision support systems, indexes and other business intelligence system components. 

Business intelligence analysts can be great at what they do, but without professional branding, they may not be recognized outside their own circle. Branding is about demonstrating competency and shaping industry discussions. Those entering this field can use LinkedIn to accomplish personal branding by:

• Optimizing their profiles with a strong headline and an “about” section that demonstrates key accomplishments and expertise
• Posting regularly and creating industry-related content pillars
• Creating a digital portfolio with LinkedIn’s “Featured” section
• Strategically connecting with professionals in the same field

Want to learn more about business intelligence analyst skills? University of Phoenix offers a variety of online technology degrees, including the Bachelor of Science in Data Science.

To explore these degree programs, reach out to UOPX to request information.

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