Become a Data Analyst
Everything you need to know; What data analysts do, what tools they use, and exactly how to start building your skills.
Code. Report. Analyse. Excel
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What Does a Data Analyst Actually Do?
Data Analysts collect, clean, and analyse data to uncover trends and help businesses make smarter decisions. Here we break down areas of the role.
Analyse, Model, and Visualise Data (20 - 25%)
Here’s where your core analytical skills kick in; running calculations, creating pivot tables or dashboards, spotting trends, building reports, and digging into patterns. Reconciliation forms a large of this time too, ensuring analysis is accurate.
Working Example: Using Power BI to build a sales pipeline dashboard and translating that into a forecast.
Present and Iterate with Feedback (15 - 20%)
Your analysis doesn't remain in isolation. Once you deliver it, expect questions, requests for tweaks, and follow-ups. Clear communication, visual storytelling, and the ability to explain insights simply are just as important as technical skills, and data preparation.
Working Example: You present a dashboard to a board of directors, then revise it after feedback to highlight customer lifetime value instead of just sales volume.
Collaborate with Stakeholders (25 - 30%)
You’ll spend a big chunk of your time working with people; sales managers, product owners, finance teams, and marketing leads to understanding what questions they need answered. Analysts are translators between the business and the data.
Working Example: A sales manager might ask why sales dropped last week. You’ll help frame the right questions, pull the data, and surface an answer.
Gather, Clean, and Prepare Data (30 - 40%)
No matter the tools you use (Excel, SQL, Python), you’ll be preparing raw, messy data. That means combining sources, fixing errors, filtering irrelevant rows, and making sure it’s usable. This is often the most time-consuming but essential parts of the job.
Working Example: Merging multiple CSV files from a CRM export, removing duplicates, and preparing monthly sales data for analysis.
Who Do Data Analysts Work With?
You won't be tucked away scripting queries or preparing data all day. Analysts shape strategy, clarify problems, and influence decisions, through data. You’ll work with:
Sales & Marketing Teams - to track performance, leads, and revenue drivers
Operations & Finance - to optimise costs, efficiency, and cash flow
Product Managers & Founders - to identify what’s working and what needs fixing
IT & Technical Teams - to ensure security and infrastructure is prepared for a data landscape
Foundational Skills
Excel
Excel is still the most used tool in real world data jobs. It’s quick, flexible, and used for everything from organising messy datasets to running ad-hoc analysis. Knowing pivot tables, conditional formatting, VLOOKUP/XLOOKUP, and formulas is a must.
Why It Matters?
These are the core skills you’ll need to become job ready, and we've provided some recommended resources to help get you prepared
SQL
SQL (Structured Query Language) lets you talk to databases. Every analyst role expects you to write queries; it’s how you pull the data before analysis or visualisation. SELECT statements and WHERE clauses are the query anchors
Where to Start
Why It Matters?
Excel for Data Beginners
Where to Start
SQL for Beginners
Calculating columns with formulas
Pivoting data for aggregations
Cleaning raw CSV data before importing to SQL
Running month-on-month growth comparisons
Budget tracking and sales analysis
Real World Use Cases
Pro Tip
Excel remains the go-to tool for stakeholders, being confident and fluent helps you communicate results clearly, to any audience.
Excel Bible for Analysts
Excel Essentials
Real World Use Cases
Pro Tip
Pulling sales by area for the last 6 months
Filtering customers by activity
Joining tables (customers | sales | products)
Creating views for repeatable queries
Adhoc datatset queries for short term analysis
Learn how to write JOINs, GROUP BY, and CASE statements, as well as logical assumptions, these cover 80% of daily use.
Mode SQL Tutorial
SQL Bootcamp
Reporting Tools
These tools let you create dashboards and visual reports. They’re essential for showing insights in a way non-technical teams understand. Power BI is widely used in corporate and Microsoft environments, while Tableau is strong in enterprise and startups.
Why It Matters?
Soft Skills
You don’t just need to run the numbers, you need to understand what they mean, and how they are impacted. This means spotting trends, checking assumptions, understanding KPIs, and translating data into actionable insights.
Why It Matters?
Visualising monthly sales by team
Creating interactive dashboards for managers
Making KPIs easy to track over time
Data calculations in semantic models
Curating business access to data
Real World Use Cases
Pro Tip
Start with Power BI if you work in a Microsoft organisation; it’s free and integrates seamlessly with Excel and SQL.
Real World Use Cases
Pro Tip
Presenting insights to managers or board
Noticing when averages hide outliers
Digging into causes of results change
Spotting opportunities in weekly sales data
Talking confidently to all stakeholders
The best analysts aren’t the ones who code best; they’re the ones who can articulate complex things simply, to technical, commercial or operational areas.
Where to Start
Power BI for Beginners
Where to Start
Storytelling with Data
Tableau for Beginners
PowerBI A-Z
Data Visualisation
Data Literacy Crash Course
Advanced Skills
Advanced SQL
SQL isn’t just for pulling tables, advanced SQL lets you clean, transform, automate and analyse data inside a data warehouse, reducing dependancy on front end reporting. Advanced analysts can prepare data efficiently, as well as analyse it.
Why It Matters?
These are the aspirationl skills you’ll need to excel as a Data Analyst or prepare to transition into a more advanced role
Python
Python brings automation and deeper analytics to your toolkit. It’s ideal for cleaning complex datasets, building repeatable workflows, and expanding into things like forecasting, scraping, or custom reports. It also allows integration into external applications.
Where to Start
Why It Matters?
SQL Cookbook
Where to Start
Python practices
CTEs (Common Table Expressions) for queries
Case statements for logic, sorting or simplifying
Views ready for dashboards without further prep
Stored Procedures to automate transformations
Deep data interrogation for enhanced forecasts
Real World Use Cases
Pro Tip
Learn SUM, COUNT, RANK, LEAD, PARTITION BY, HAVING and nested queries; they’re commonly used in SQL scripts, views and procedures.
Advanced SQL
Real World Use Cases
Pro Tip
Automating Excel reports using Python scripts
Analysing trends in activity over time with pandas
Creating repeatable functions to model data
Ingesting large datasets for forecast prediction
API integration for SQL table queries
Focus on pandas, numpy, and matplotlib first; these libraries do 80% of the work analysts need, and solve real data problems fast.
Python for Data Analysts
Cloud Data Tools
More companies are moving their data to the cloud. Tools like Google BigQuery, AWS Redshift, and Snowflake centralise data and make it scalable, fast, and secure. Analysts who understand data warehouses push analysis forwards and are in high demand.
Why It Matters?
Advanced Reporting
Dashboards aren’t just visuals, they’re decision making tools. Curating an advanced, interactive, and business-aligned reporting suite in Power BI or Tableau sets you apart from entry-level analysts, and fosters a data orientated culture.
Why It Matters?
Querying massive datasets in BigQuery using SQL
Connecting cloud data for real time dashboards
Reduce local datasets by centralising in the cloud
Join multiple source applications for insights
Allow multiple users access to cloud datasets
Real World Use Cases
Pro Tip
Start with BigQuery, it uses standard SQL, scales automatically and integrates seamlessly with Looker Studio, Excel.
Real World Use Cases
Pro Tip
Building dashboards with slicers and bookmarks
Using DAX for KPIs and smart visuals
Mobile-friendly views for field teams or execs
Optimising query performance for speed
Allowing user input directly to report pages
Every stakeholder wants a single source of truth. Learn how to structure your reports to build trust and clearly answer business questions.
Where to Start
BigQuery: Definitive Guide
Where to Start
Data Visualisation
ADF Cookbook
Advanced PowerBI & DAX
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