Learning a new skill can be exhausting, especially when there are too many resources available and you have no idea where to begin. To help you through this, this article provides a clear Data Analyst roadmap for the year 2025.
This Data analyst roadmap will be divided into two sections. The first section talks about skills and technologies to learn at the initial stage when you have zero idea about Data Analysis. Learning the skills suggested in this section will help you start applying to major companies looking for entry-level data analysts.
The second section will discuss some advanced topics and skills you need to learn while applying for a job. In this article, we will not be discussing the intermediate to advanced level Data analyst roadmap, as it will become more confusing. Next article will cover the intermediate to advanced level topics to learn. Let’s start your Data Analyst roadmap for this year.
NOTE: LIST OF FREE CERTIFICATIONS AND COURSES ARE MENTIONED BELOW
Data Analyst roadmap: Beginners to Intermediate Level
To getting started as a Data analyst, one needs to learn these four major skills listed below.
- Excel: For a beginner to advance level data analysis, one needs to get familiar with Excel. Not everything is necessary to learn in Excel for analyzing data. There are a few topics that one needs to master at least to start analyzing the data.
- SQL: SQL referred to as Structured Query Language, is a database language used to fetch data from the databases.
- Basic Math: Analyzing data and finding trends in it requires some knowledge of math. If you’re someone who doesn’t like math, but still to get a job as a Data analyst, you need to learn some of the topics of mathematics like statistics, probability, and graphs.
- Visualization tools: Now, the last part to become an intermediate level Data analyst, one must be familiar with any of the visualization tools. Every data has a story, and the story must be represented in the form of visuals for normal people. Data needs to be converted into pictorial form to make some sense of it.
1. Excel for Data Analysis
| Week | Topics |
|---|---|
| Week 1 | In first week, focus on topics like data cleaning and text functions. After learning data cleaning, start learning basic excel formulas (SUM, AVERAGE, IF, VLOOKUP). Then, learn sorting and filtering the data. |
| Week 2 | In the second week for your data analyst roadmap, learn about pivot tables, and pivot charts. Start practicing with creating basic dashboards using tables and charts. Learn and master conditional formatting and advanced formulas of excel(SUMIFS, COUNTIF, AVERAGEIF). |
| Week 3 | Now, you have learned all the basics, start working on Data Aggregation using grouping and SUBTOTAL functions in excel. Practice making charts and learn which visualization method is best for different datasets. |
| Week 4 | Now, in your last week, learn techniques to import and export the data. Learn about macros. Practice as much as possible by making dynamic dashboards and integrating everything learned up to now. |
Resources to learn
- Learn and make notes using excel-easy site. It covers everything you’ll need on your journey.
- For dummy dataset to practice, one can refer Kaggle.
2. Learning SQL
| Week | Topics |
|---|---|
| Week 1 | Master basics of SQL Syntax, SELECT statements, WHERE clause, ORDER BY, and basics of aggregate functions like COUNT, SUM, and AVG. |
| Week 2 | Learn and master JOINs. (INNER JOIN, OUTER JOIN, RIGHT JOIN, LEFT JOIN and FULL JOIN). Learn using GROUP BY and HAVING clauses. Practice basic data manipulation in SQL that are INSERT, UPDATE and DELETE. |
| Week 3 | Work on different data types in SQL (text, date and numeric functions). |
| Week 4 | Now, for the last week, focus on Window functions and case statements. |
Resources to learn
- Refer Mode website for learning SQL from basics.
- For interactive learning (practicing), you can refer SQL Bolt.
3. Understanding Basic Mathematics
| Week | Topics |
|---|---|
| Week 1 | Basic arithmetic operations, percentages and averaged (Mean, median and mode). Practice these operations on small datasets. |
| Week 2 | Learn ratios and proportions, understand basic algebra. |
| Week 3 | Learn Basic probability and data distribution. |
| Week 4 | Learn about growth concepts, percentiles, quartiles and Rate of change. |
Resources to learn
- Refer to Brilliant for learning Basics of Math in 23 lessons.
4. Getting familiar with Visualization Tools
There are many visualization tools available and some of them are quiet popular among Data Analyst. One of the popular tool for visualizing large volume of data is Power BI. In this article, we will be discussing about Power BI tool for data visualization.
| Week | Topics |
|---|---|
| Week 1 | Learn to Install Power BI and get familiar with the interface. Learn to import data from Excel and SQL. Learn and practice Power Query for cleaning and transformation of the data. |
| Week 2 | Learn about data modeling, understand relationships, and learn about Primary key, foreign keys. Learn and practice DAX basics. |
| Week 3 | Learn various data visualization techniques (Create charts, use slicers, apply conditional formatting) Practice designing interactive reports and share them in Power BI Service. |
| Week 4 | Practice a lot by creating dashboards and understanding other features like sharing and collaboration. If still you have sometime, learn some advanced features like Bookmarks, Drill-downs and what-if parameters. |
Resources to learn
- Refer to this Power BI video on YouTube by Alex the Analyst, to learn and create small projects using Power BI. Click here to watch it.
List of Courses and certifications
- Learn to code for data analysis by OpenLearn. (Free Certification available after completion of this course).
- Free data analytics courses by Great Learning. (While the content of course is free, certification is paid).
- Unlimited Data Analyst Bootcamp by Alex the Analyst. (24 hours long available video on YouTube).
Conclusion
In this article, we discussed topics to cover to start your journey as a Data Analyst from zero. Topics that are necessary have been covered in this, so one doesn’t have to get confused and learn unnecessary topics. We’ve also provided links to free courses and certification, along with all the required resources to get started. In the upcoming article, we will be covering ‘Data analyst roadmap: Intermediate to Advanced level’, where we will discuss Python, Python libraries, and cloud platforms required for data analysis.