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Business Intelligence Analyst

Building the reports and dashboards that help organisations understand their performance

Also known as:BI AnalystReporting AnalystBI DeveloperData Insights AnalystBusiness Analytics Analyst
Stable

Business Intelligence Analyst Salary

United Kingdom

£35,000 – £65,000

United States

$65,000 – $110,000

Varies by location, sector, and experience. Last updated: 2025.

What Is a Business Intelligence Analyst?

A Business Intelligence Analyst designs and maintains the reports, dashboards, and data models that help organisations understand their performance. They work with business stakeholders to understand what questions need answering, connect to the relevant data sources, and build outputs that are clear, accurate, and easy to act on. The role exists across almost every sector with measurable operational data — retail, financial services, logistics, healthcare, and media are particularly active — and is widely employed outside pure technology businesses.

The role sits closer to the business than a Data Engineer or Analytics Engineer — the primary output is insight rather than infrastructure. BI Analysts spend significant time understanding business processes, translating requirements into reporting logic, and ensuring that the dashboards they build are actually used. In practice this means working primarily in tools such as Power BI, Tableau, or Looker, writing SQL against warehouse platforms such as Snowflake or BigQuery, and iterating on outputs with business owners. Strong SQL skills, proficiency in at least one BI tool, and clear communication with non-technical stakeholders are the core requirements.

What Does a Business Intelligence Analyst Do?

  • Design and build dashboards and reports in Power BI, Tableau, or Looker to meet defined business reporting needs
  • Write SQL queries to extract, transform, and validate data from warehouse and database sources for reporting use
  • Gather reporting requirements from business stakeholders and translate them into data model and visualisation specifications
  • Maintain and improve existing reports as business needs, data structures, and metric definitions evolve over time
  • Identify data quality issues affecting report accuracy and work with data engineering teams to resolve them at source
  • Present findings and support stakeholders in interpreting data outputs and making decisions based on reported metrics

Business Intelligence Analyst Skills

Hard Skills

  • SQL
  • Reporting and Visualisation
  • Data Modelling
  • Data Analysis
  • Requirements Gathering
  • Data Quality Management
  • Stakeholder Management
  • KPI Development
  • Statistical Modelling

Soft Skills

  • Analytical ThinkingTranslating business questions into reporting logic
  • CommunicationPresenting dashboard findings to non-technical teams
  • Stakeholder ManagementManaging competing reporting requests
  • Attention to DetailEnsuring data accuracy across reports and models
  • User EmpathyDesigning dashboards people will actually use
  • PrioritisationFocusing build effort on highest-value reporting needs

Business Intelligence Analyst Tools & Software

How to Become a Business Intelligence Analyst

Typical Route

Most BI Analysts hold a bachelor's degree in Business, Economics, Mathematics, Statistics, or Computer Science. The role is among the more accessible data positions for graduates from non-technical disciplines — SQL and visualisation skills, often developed independently or through electives, matter as much as the degree subject. Many analysts also enter through associate degree programs in business or data analytics at community colleges before developing BI-specific skills on the job. A master's degree in Business Analytics or Data Science supports senior progression.

Alternative Route

Microsoft Power BI Data Analyst (PL-300) and Tableau Desktop Specialist are the most directly relevant entry credentials and are widely listed in US job descriptions. Google Data Analytics Professional Certificate provides a structured entry-level learning path. Microsoft Learn delivers free PL-300 preparation; Pluralsight and Coursera offer instructor-structured Power BI and Tableau training. Many BI Analysts transition from Excel-heavy reporting or business analyst roles — a portfolio of dashboard and SQL work is typically more persuasive to employers than certifications alone.

A Day in the Life of a Business Intelligence Analyst

Morning

Meet with the operations director to understand the requirements for a new supplier performance dashboard, clarifying which delivery metrics matter most and what the acceptable data latency is
Investigate why last Friday's weekly sales report showed a 12% revenue figure the sales team cannot reconcile with their CRM export
Write the SQL model that joins the orders, returns, and product tables to produce the net revenue by category dataset the new operations dashboard will be built on

Afternoon

Build the supplier performance dashboard in Power BI, configuring the on-time delivery, defect rate, and lead time visuals agreed this morning
Present the draft dashboard to the operations director and two regional leads, capturing their feedback on the date filter behaviour and the missing breakdown by warehouse location
Document the metric definitions for the five KPIs in the new dashboard, writing clear business-language descriptions that non-technical users can find in the shared data dictionary

Business Intelligence Analyst Career Path

Reporting Analyst / Junior BI

0–2 yrs

→

BI Analyst

2–4 yrs

→

Senior BI Analyst

4–6 yrs

→

BI Lead / Analytics Engineer

6–8 yrs

→

Head of BI / Data Manager

8+ yrs

Business Intelligence Analyst Job Outlook

Stable

BI remains a consistent hiring area across enterprise, financial services, retail, and the public sector — organisations always need reliable reporting capability. The role is evolving: analysts who develop modern data stack skills — particularly dbt and cloud warehouse platforms — alongside traditional BI tool expertise find stronger progression opportunities. Demand is unlikely to contract, but practitioners anchored to legacy tooling face a narrowing opportunity set as organisations modernise their data infrastructure.

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