BI Analyst Resume Keywords: SQL & Data Modeling (2026)

Business intelligence analyst resumes need keywords spanning BI tools, databases, data modeling, and business terminology. Missing keywords in any category reduces your ATS match score.

Most BI resumes cover tool names but miss data modeling, ETL, and business context keywords that differentiate senior candidates from beginners.

Find exact formulas for turning these keywords into quantified impact bullets in our Professional Impact Dictionary.

BI Tools Keywords

Visualization Platforms

Tableau
Tableau Desktop
Tableau Server
Tableau Online
Tableau Prep
Power BI
Power BI Desktop
Power BI Service
DAX
Power Query
Looker
LookML
Qlik Sense
QlikView
Metabase
Mode Analytics
Sisense
Domo

Excel & Spreadsheets

Microsoft Excel
Advanced Excel
Pivot tables
VLOOKUP / XLOOKUP
Power Pivot
Power Query
Macros
VBA
Google Sheets
Data validation
Conditional formatting

Reporting

Dashboard design
Dashboard development
Interactive dashboards
Self-service analytics
Self-service reporting
Ad-hoc reporting
Automated reporting
Scheduled reports
Executive dashboards
KPI dashboards
Scorecards
Report automation

SQL & Database Keywords

SQL

SQL
Advanced SQL
Complex queries
Subqueries
CTEs (Common Table Expressions)
Window functions
Aggregate functions
Joins (INNER, LEFT, OUTER, CROSS)
UNION
GROUP BY
HAVING
CASE statements
Stored procedures
Views
Materialized views
Query optimization
Query performance tuning

Data Warehouses

Snowflake
BigQuery
Amazon Redshift
Azure Synapse
Databricks
Teradata
Oracle
SAP BW
Data warehouse
Data lake
Data lakehouse
Cloud data warehouse

Databases

PostgreSQL
MySQL
Microsoft SQL Server
Oracle Database
MongoDB
DynamoDB
SQLite

Data Modeling Keywords

Modeling Concepts

Data modeling
Dimensional modeling
Star schema
Snowflake schema
Fact tables
Dimension tables
Slowly changing dimensions
Entity-relationship model
Normalization
Denormalization
Semantic layer
Metrics layer
Data ontology

Modeling Tools

dbt
dbt Cloud
dbt Core
Erwin
Lucidchart
dbdiagram
SQL modeling
Version-controlled models
Data transformation
Data lineage

ETL & Data Pipeline Keywords

ETL Tools

ETL
ELT
Airflow
Apache Airflow
Fivetran
Stitch
Talend
Informatica
SSIS
Matillion
Airbyte
Meltano

Pipeline Concepts

Data pipeline
Data integration
Data ingestion
Data extraction
Data transformation
Data loading
Batch processing
Real-time processing
Streaming data
Data orchestration
Workflow automation
Scheduled jobs
Data refresh

Data Quality

Data quality
Data validation
Data cleansing
Data profiling
Data governance
Data catalog
Data dictionary
Master data management
Data stewardship
Data accuracy
Data completeness
Data consistency

Analytics Keywords

Analysis Types

Business analysis
Data analysis
Trend analysis
Cohort analysis
Funnel analysis
Customer segmentation
Market analysis
Competitive analysis
Variance analysis
Root cause analysis
Predictive analysis
Prescriptive analysis
Exploratory data analysis

Metrics & KPIs

KPIs
Key performance indicators
Metrics
OKRs
Business metrics
Revenue metrics
Customer metrics
Operational metrics
Financial metrics
Marketing metrics
Sales metrics
SaaS metrics
MRR / ARR
Churn rate
CAC
LTV
Conversion rate
NPS

Statistical Concepts

Statistical analysis
Regression analysis
Correlation
A/B testing
Hypothesis testing
Confidence interval
Statistical significance
Forecasting
Time series analysis
Probability
Distribution analysis

Programming Keywords

Python

Python
pandas
NumPy
matplotlib
seaborn
Jupyter Notebook
scikit-learn
SciPy
Data manipulation
Data wrangling

R

R
R Studio
ggplot2
dplyr
tidyverse
Shiny

Other

Git
GitHub
Version control
API integration
REST API
JSON
XML
CSV
Markdown
Command line

Business Domain Keywords

Cross-Industry

Business intelligence
Business analytics
Decision support
Strategic insights
Data-driven decisions
Actionable insights
Executive reporting
Board reporting
Monthly business review
Quarterly business review
Annual planning
Budget analysis

Stakeholder Terms

Stakeholder management
Requirements gathering
Business requirements
User requirements
Cross-functional collaboration
Data storytelling
Presentation skills
Executive communication
Training
User adoption
Self-service enablement

Action Verbs for BI Analysts

For Analysis

Analyzed
Identified
Discovered
Uncovered
Quantified
Measured
Evaluated
Assessed
Investigated
Profiled

For Building

Built
Created
Designed
Developed
Implemented
Architected
Modeled
Automated
Configured
Deployed

For Impact

Drove
Enabled
Informed
Influenced
Improved
Optimized
Reduced
Increased
Saved
Transformed

Keywords by Seniority

Junior BI Analyst (0-2 years)

SQL
Tableau or Power BI
Excel
Dashboard creation
Report generation
Data validation
Ad-hoc analysis
Basic ETL
Data entry
Data cleaning

Mid-Level BI Analyst (3-5 years)

Advanced SQL
Multiple BI tools
Data modeling
dbt
ETL pipeline
Stakeholder management
Self-service analytics
KPI framework
Cross-functional analysis
Snowflake or BigQuery

Senior BI Analyst (6+ years)

BI architecture
Data strategy
Semantic layer
Data governance
Analytics platform
Team mentoring
Executive reporting
Data infrastructure
Tool evaluation
Center of excellence

Quick Reference: Top 40 BI Analyst Keywords

SQL
Tableau
Power BI
Dashboard
Data analysis
Business intelligence
Data modeling
Snowflake
BigQuery
ETL
dbt
KPIs
Reporting
Data warehouse
Python
Excel
Data visualization
Self-service analytics
Stakeholder management
Star schema
Data quality
Data governance
Airflow
Fivetran
Looker
Metrics
A/B testing
Cohort analysis
Revenue analysis
Customer segmentation
Forecasting
Cross-functional
Requirements gathering
Data pipeline
Cloud platform
Redshift
Query optimization
Automated reporting
Data dictionary
Executive dashboards

Build your ATS-optimized BI analyst resume with the right keywords

Keyword Strategy for BI Analysts

SQL Is Non-Negotiable

SQL appears in virtually every BI analyst job description. Include "SQL" in your skills section and demonstrate complexity in your experience bullets. "Advanced SQL" or "Complex SQL" are worth including alongside specific techniques (CTEs, window functions, query optimization).

Match Tool Names Exactly

Write "Tableau Desktop" not "data visualization." Write "Snowflake" not "cloud data warehouse." ATS systems match on exact product names. If the posting says "Power BI," include "Power BI" specifically.

Include Both Analysis and Infrastructure Keywords

Junior BI analysts focus on dashboard creation keywords. Senior BI analysts add data modeling, ETL, and data governance keywords. Include both to signal readiness for complex BI work.

Quantify Every Analytics Keyword

"Data analysis" in your skills section needs "Analyzed customer churn data identifying 3 leading indicators, enabling retention program that reduced churn by 15% ($1.2M annual impact)" in your experience section. Unquantified analytics keywords signal theoretical knowledge rather than proven capability.

Separate Technical and Business Keywords

BI analysts bridge two worlds: technical data work and business decision support. Your resume should have keywords from both sides. Technical keywords (SQL, dbt, Snowflake, data modeling) prove you can build reliable analytics infrastructure. Business keywords (stakeholder management, executive reporting, KPI framework, data storytelling) prove you can translate data into decisions. Missing either category makes you look like either a pure technician or a pure communicator, when the value of a BI analyst is being both.

Signal Modern Stack Proficiency

The BI landscape has shifted significantly toward cloud-native tools and the modern data stack. If you have experience with Snowflake, dbt, Fivetran, and Looker, prioritize these keywords over legacy tools. Hiring managers scanning for modern BI capabilities will immediately recognize this stack as current and relevant.

For full resume structure, formatting, and examples, see our Business Intelligence Analyst Resume Guide.

BI Analyst Resume Keywords: SQL, Tableau & Data Modeling