Data Analysis for Beginners

Data Analysis for Beginners teaches, on Breni, how to answer business questions with data using the tools analysts use daily: spreadsheets, SQL and dashboards. Unlike the data science path, it does not build predictive models. Its 8 courses cover the analysis process, descriptive statistics, data cleaning, charts, funnels, retention and presenting results. Learners finish able to pull data with SQL, build a pivot table and a dashboard, and write a clear recommendation. Tools are taught before business cases, each course unlocking once the previous one is done.

  • 8 courses
  • 14 learning objectives
  • Level: beginner
  • Language: English
  • Price: Subscription, free trial

What you will be able to do

  • Turn a vague business question into a measurable KPI and an analysis plan
  • Summarise sales or user data with pivot tables, lookups and percentage change
  • Write SQL queries that filter, group and join tables to answer a question
  • Build a dashboard that shows the few numbers a manager needs
  • Analyse a sales funnel or customer retention and explain what changed
  • Present findings as a short written summary with a recommendation

Full curriculum

Part 1 · Thinking like an analyst

1. The Data Analysis Process: From Question to Decision

Follow the steps analysts use to go from a question to a decision. Units, in order: Ask, prepare, process, analyse, share and act; Writing a question data can answer; Choosing KPIs; Where business data comes from; What a data analyst does day to day.

  • — The Daily Analyst Routine
    Learn what data analysts do every single day.
    • Analyst Job Basics
    • Bridging Raw Data and Decisions
  • — The Ask Phase
    Learn how to define problems and choose key metrics.
    • Writing Good Questions
    • Choosing Key Performance Indicators
  • — The Prepare Phase
    Discover where business data comes from and how to collect it.
    • Finding Business Data Sources
    • Data Collection Basics
  • — The Process Phase
    Clean and organize raw data to remove errors.
    • Spotting Data Errors
    • Cleaning Raw Data
  • — The Analyze Phase
    Find patterns, trends, and relationships in clean data.
    • Finding Trends and Patterns
    • Answering Business Questions
  • — The Share Phase
    Communicate your findings using clear charts and dashboards.
    • Building Simple Charts
    • Telling Stories With Data
  • — The Act Phase
    Turn analysis results into smart business decisions and actions.
    • Making Data Driven Decisions
    • Tracking Project Success

2. Descriptive Statistics for Analysts

Describe data with the handful of numbers that matter in business reports. Units, in order: Averages and when the median is better; Percentages and percentage change; Spread and distributions; Outliers; Segmenting results by group.

Part 2 · Analyst tools

3. Spreadsheets for Analysis

Use spreadsheet formulas, lookups and pivot tables to summarise data. Units, in order: Sorting and filtering; Formulas for totals, counts and averages; Pivot tables; Lookups between two sheets; Conditional formatting to flag results.

4. SQL for Analysts

Pull exactly the data you need from a database with SQL. Units, in order: SELECT and WHERE; GROUP BY and aggregates; Joining tables; CASE for grouping values; Working with dates.

5. Preparing Data for Analysis

Get messy data into a consistent shape before analysing it. Units, in order: Checking data types; Handling blanks and duplicates; Standardising names and categories; Combining data from several sources; Documenting what you changed.

6. Charts and Dashboards

Build charts and dashboards that answer a question at a glance. Units, in order: Choosing the right chart; Dashboard layout and hierarchy; Filters and drill-downs; Tableau and Power BI compared; Removing clutter.

Part 3 · Analysis at work

7. Analysing Business Questions

Apply common analysis patterns to sales, marketing and product data. Units, in order: Funnel analysis; Cohort retention; Reading A/B test results; Trends and seasonality in sales; Finding the cause of a sudden drop.

8. Presenting Findings

Explain results so that people who were not in the analysis can act on them. Units, in order: Leading with the answer; Writing a one-page summary; Turning findings into recommendations; Slides that support the story; Handling questions and doubts.

Sample: The Data Analysis Process: From Question to Decision

The opening tier, (The Daily Analyst Routine). Learn what data analysts do every single day.

Analyst Job Basics

Understand core daily tasks and responsibilities of an analyst.

Bridging Raw Data and Decisions

See how analysts turn raw numbers into business value.

Questions about Data Analysis for Beginners

Can I learn data analysis with no experience?

Yes. Data Analysis for Beginners on Breni starts with how analysts frame questions and teaches spreadsheets and SQL from the beginning.

Is data analysis the same as data science?

No. Data analysis explains what happened and why, mostly with spreadsheets, SQL and dashboards. Data science adds predictive models, which the Data Science for Beginners path covers.

Do I need to learn Python for data analysis?

Not for this path, which uses spreadsheets, SQL and dashboards. Python becomes useful later for larger datasets and automation.

How long does it take to learn data analysis?

It depends on how often you practise. Breni lessons take about three minutes each and the 8 courses are self-paced.

Do I get a certificate for this data analysis course?

Yes, finishing the path earns a Breni certificate of completion. It is not a degree or a professional credential.

Related learning paths

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