How to Learn Data Analytics from Scratch: Step-by-Step Roadmap for Beginners

 How to Learn Data Analytics from Scratch | Roadmap




Learning Data Analytics from scratch may seem confusing at first because the field contains several technologies and concepts. Beginners look at SQL, Python, Excel, statistics, Power BI and databases and have no idea from where to start.

  • The good news is that you do not need to learn everything at once
  • A structured roadmap can make things easy for you.
  • Start With Data Fundamentals

Before learning tools, understand what data really means

Learn concepts like:

  1. Structured and unstructured data
  2. Numerical and categorical data
  3. Tables
  4. Variables
  5. Records
  6. Data sources
  7. Data quality
  8. Missing values
  9. Duplicates

This will make your learning curve seamless as you will comprehend concepts faster.

Learn Excel

Excel is a good place to start because you will be able to work with data right away.

  1. Learn SUM
  2. AVERAGE
  3. COUNT
  4. IF
  5. SUMIF
  6. COUNTIF
  7. XLOOKUP
  8. Pivot tables
  9. Charts
  10. Data validation

Do small projects like analyse monthly sales. You can also try creating small dashboards.

Understand Statistics

Statistics helps you derive meaning from your data.

Say you are comparing two teams based on their average monthly sales.

Team A has an average monthly sale of ₹10 lakh

Team B has an average monthly sale of ₹10 lakh

Can you say both teams are equal performers? No

Not really! One team can be more consistent than the other. Statistics helps you identify this.

Learn SQL

Now that you are comfortable analysing spreadsheets, learn SQL.

This query language has immense importance because most organisations store data in databases. You will learn to write queries to extract data from databases.

Practice queries like:

  1. Show me the list of customers
  2. Show me all transactions for a particular customer
  3. Total sales for a month
  4. Sales grouped by a particular segment
  5. Join two tables
  6. Find duplicates
  7. Ranking queries
  8. Avoid practicing SQL only for the syntax. Practice solving problems.

Learn Python for Analytics

Python helps you deal with larger data sets. It helps you automate repetitive tasks.

  1. You can learn variables
  2. lists
  3. dictionaries
  4. conditions
  5. loops
  6. functions
  7. files

Once you are comfortable with these concepts, you can install libraries like NumPy, pandas, Matplotlib and Seaborn to perform analytics.

The aim is to do analytics using Python and not to build applications.

Learn Power BI

Now that you know how to prepare data, the next step is to present this data in a visually appealing manner.

Create reports and dashboards that have:

  1. KPIs
  2. Bar graphs
  3. Line graphs
  4. Tables
  5. Visualization slicers
  6. Trend analysis

A good dashboard answers a question. It does not merely make the report look good.

Work on Projects

Projects will give you an opportunity to demonstrate your skills. As a beginner, you can start with building these kinds of projects:

  1. Retail Sales Dashboard
  2. Analyse revenue, profit, products and regions
  3. Customer Analysis
  4. Understand customer buying patterns
  5. Employee Analysis
  6. Analyse attrition, departments and compensation
  7. Marketing Analysis
  8. Compare performance of campaigns

Create a Portfolio

Your portfolio should give a visitor an insight into what you did in a project rather than merely display images of your projects.

Create a page for each project that includes:

  1. Project objective
  2. Dataset
  3. How the data was cleaned
  4. SQL queries used
  5. Analysis performed
  6. Dashboard created
  7. Insights gained
  8. Recommendations

Explain what you discovered instead of merely displaying images.

Learn Data Analytics with Quality Thought

Quality Thought IT Training Institute offers Data Analytics as part of their Data Science & Analytics training portfolio. The comments section on their website mentions training in Statistics, Python, SQL, Excel and Power BI.

For absolute beginners, a guided program can help them get a sequence of steps rather than leaving them to figure out what to learn and when.

Conclusion

The best way to learn Data Analytics from scratch is to take up this progressive path: 

Fundamentals → Excel → Statistics → SQL → Python → Power BI → Projects → Portfolio → Interview preparation. 

Do not get in a hurry. Analytics is all about practice and problem-solving.

Course Details: 

Contact : info@qualitythought.in

Call:  07330999080

Directions:  (Get Directions)



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