Data Analyst
O*NET-SOC: 15-2051.00
Develops and applies techniques of data analysis, data mining, machine learning, and statistics to large structured and unstructured datasets to extract meaningful insights for business decision-making.
About this Role
Data analysts turn raw numbers into actionable insights by cleaning, transforming, and modeling data to answer business questions. They spend much of their day in tools like SQL, Python, Excel, and visualization platforms such as Tableau or Power BI, pulling data from databases, joining tables, and building dashboards that track KPIs like sales, user engagement, or operational efficiency. A data analyst might define a weekly report format, then refine the logic if stakeholders notice anomalies or request new metrics.
A Day in the Life
9:00 AM
Scan email inbox and Slack
Review overnight messages, urgent requests from stakeholders, and any alerts from automated dashboards or data pipelines before deciding which tasks to prioritize.
9:30 AM
Query and clean data
Write or refine SQL queries to pull data from a database, then use Python or spreadsheet tools to clean outliers, missing values, and duplicate records for an upcoming report.
11:00 AM
Build or update a dashboard
Connect cleaned data to a Tableau or Power BI worksheet, create filters, add calculated fields, and design charts that highlight key trends for a weekly performance review.
12:30 PM
Lunch and light reading
Step away from the screen, then browse a short article or blog post on data storytelling or a new feature in a visualization tool to stay current.
1:30 PM
Attend a stakeholder meeting
Join a meeting with product or marketing to walk through the latest dashboard, explain what changed, and clarify what new metrics or slices of data leadership wants to see.
3:00 PM
Run exploratory analysis
Dig into a one-off question-such as a sudden drop in sign-ups-by segmenting data by channel, region, or cohort and testing hypotheses with simple statistical checks.
4:30 PM
Document and version changes
Update a README or internal wiki page describing the logic for a new metric, then commit SQL or Python scripts to version control with clear comments.
5:30 PM
Wrap up pending tasks
Send a summary email to stakeholders with updated numbers, schedule recurring reports, and flag any data quality issues that developers or engineers need to address.
Tools & Technologies
Databases & Data Tools
- AWS
- PyTorch
- SQL
- AWS EC2
- Amazon Redshift
Programming Languages
- C++
- Java
- Python
- R
- C#
Database Systems
- Apache Hadoop
- Apache Cassandra
- Apache Hive
- Elasticsearch
- MongoDB
Development Tools
- Microsoft Azure
- Apache Kafka
- C
- Go
- Ruby
Analytics & Science
- SAS
- TensorFlow
- The MathWorks MATLAB
- IBM SPSS Statistics
- Google Looker Analytics
Business Intelligence
- Apache Spark
- Microsoft Power BI
- Tableau
- Alteryx
- MapReduce big data software
Salary Details
Salary Distribution
Most professionals earn between $83K and $156K
| Percentile | Salary |
|---|---|
| 10th | $64K |
| 25th | $83K |
| 50th (Median) | $113K |
| 75th | $156K |
| 90th | $194K |
Certifications & Training
Recommended
Google Data Analytics Professional Certificate
A structured program that covers spreadsheets, SQL, data visualization, and basic statistics, often used by career changers to demonstrate foundational data analysis skills.
Microsoft Certified: Data Analyst Associate
Microsoft
Validates ability to use Power BI to model, visualize, and share data insights, including creating reports and dashboards for business users.
Helpful
Tableau Data Analytics Certification
Tableau
Assesses skills in connecting to data sources, building interactive dashboards, and using Tableau to communicate data stories effectively.
Certified Analytics Professional (CAP)
INFORMS
A senior-level credential that focuses on the end-to-end analytics lifecycle, from problem framing to model deployment and evaluation.
Data Analytics certificate programs
Various universities and online platforms
Week-long or multi-month courses that teach SQL, Python for data analysis, and basic statistics, often used to complement formal education.
Work Environment
- Remote Work
- Fully Remote
- Work Setting
- Traditional office / indoor
- Physical Activity
- Mostly sedentary
- Social Interaction
- Highly collaborative — frequent team interaction
- Schedule
- Extended hours common
Your Skills & Attributes
Skills & Competencies Matches (47)
- Learning StrategiesModerate Match
- CoordinationModerate Match
- InstructingModerate Match
- Social PerceptivenessModerate Match
- PersuasionModerate Match
Frequently Asked Questions
Is Data Analyst a good career?
Data Analyst can be a rewarding career choice. Based on current data, the median salary is $113K and job outlook is growing (35% projected growth). Whether it's a good fit depends on your skills, interests, and values — take our quiz to find out how well you match.
What degree do you need to become a Data Analyst?
The typical education requirement for a Data Analyst is a Bachelor's Degree. However, requirements can vary by employer and specialization. Some professionals enter the field with alternative credentials or relevant work experience.
How long does it take to become a Data Analyst?
Becoming a Data Analyst typically requires about 4 years of undergraduate study. Additional time may be needed for certifications, internships, or on-the-job training depending on the specific role and employer requirements.
What is the work-life balance like for a Data Analyst?
The work-life balance for a Data Analyst is generally considered good, with reasonable hours and manageable workloads. Individual experiences vary based on employer, specialization, seniority level, and geographic location.
What is the job outlook for Data Analyst?
The job outlook for Data Analyst is growing. Employment is projected to grow by 35% over the coming decade. Labor market conditions can vary by region and specialization.