Become Job-Ready in Data Analytics Roadmap of 90 days

Key Highlights

• A 90-day data analytics roadmap gives people a clear and steady way to get ready for a job. The plan is put into three parts: foundations, core skill, and advanced application. In these 90 days, you will use and learn the main analytic tools like Excel, SQL, and Microsoft Power BI. For example, you spend the first 30 days learning the basic ideas and using simple tools. The next 30 days, you practice core skill like data cleaning and making charts using power bi dashboard and other analytic tools. In the last 30 days, you try your new knowledge by working with case studies and real projects in the world of data.

• The plan breaks down into these parts: foundations, core skills, and advanced application.

• You will learn to use important analytic tools such as Excel, SQL, and Microsoft Power BI.

• The roadmap helps you make a strong portfolio using real-world data analytics projects.

• A special practice part is set for learning SQL and making dashboards in Power BI.

• This study plan is great for students, anyone who wants to switch careers, and people who are new in the world of data.

Introduction

Are you ready to start your career in data analytics? The need for people who can use raw data and find good answers keeps going up every day. But you might ask yourself where to start. This guide will give you a simple plan for data analytics that you can follow for 90 days. When you stay with this plan, you will get the right skills, do useful projects, and get ready for your first job in data analysis. Let’s begin this journey together.

You can practice by looking for free sample dashboards on sites like Tableau Public, Kaggle, and the Power BI Community Gallery. These websites have a lot of real-world dashboard examples. You can use them through your 90-day data analytics roadmap. This will help you practice with industry tools like power bi, and get hands-on experience with data analytics and data analysis.

Data analytics roadmap 90 days:

What Is a 90-Day Data Analytics Roadmap and Who Should Use It?

A 90-day data analytics roadmap is for you if you want to learn step by step. The goal is to get you ready for work as a data analyst in about three months as data analyst in just three months. The plan breaks the world of data into easy tasks every week. You get to build new skills in a way that is simple and clear.

If you can set aside some study time in the day, this timeline is a good fit. It tells you what steps to take, so you stay on track and do not feel lost or stressed. You will spend your time learning the key skills that jobs in data analytics ask for most. This plan is a good choice for anyone who wants to get into data analytics work.

Why Choose a 90 Day Study Plan for Data Analytics Careers

A 90 day study plan for data analytics can help you stay on track. It gives you one clear way to follow so you do not feel lost. With this study plan, you will learn data analytics step by step and at your own speed. Each week, you will focus on something new. You start with the basics and move up to using new analytic tools.

This plan helps make sure you do not miss any key area. There will not be gaps in what you learn about data analytics. It also helps you feel good because you can see how far you have come, which keeps you going.

The plan is there to help you get set for entry-level data analyst roles. At first, you start with easy steps like using Excel. After that, you learn more with tasks that need SQL and Power BI. It is made to feel a lot like real work. This helps you to get used to the data analyst job and gives you hands-on skill from the start.

After 90 days, this study plan helps you build your portfolio fast. In three months, you will complete many projects and a case study. You will have real work to show what you have learned in data analytics. This is what people want when they hire for data analyst jobs. It will give you more confidence to step into a data analytics job.

Who Can Benefit: Students, Freshers, and Career Switchers

This 90-day learning plan is made for people who want to get into data analytics. It does not matter what your experience is. You will get a simple way to follow every day, so you do not feel lost about what comes next. If you want a clear study plan for data analytics, this guide will give that to you.

The roadmap is good for:

• Students who want to add real world skills over what they get at school.

• Freshers who want to make their work stand out and get seen when they look for jobs.

• People who want to switch jobs from other fields and need a simple and set way to start working in data science or analytics.

It does not matter if you are just starting work or want to change your line of work. This study plan for data analytics will help you stay on track. The plan helps you learn with good steps and makes you spend time on the things that help you get a good job in the data analytics field. In three months, you will feel more sure of yourself and your skills in data science.

Beginner’s Guide: Getting Started with Your Data Analytics Journey

To begin your path as a data analyst, you need to have a good plan. First, get to know the basic tools used in data analytics. Also, set up a place where you can learn without any trouble. This guide will take you from the starting point and help you use what you know of data mining in real situations.

Before you start to look at data sources or begin your work, you need to have the right tools. It is also good to set up a workspace where you feel comfortable and can do your best. Let’s see what you will need and how you can set up a place that helps you do well.

Tools and Resources Needed (Excel, SQL, Power BI, SocialPrachar Support)

To follow this roadmap, you need to use some important analytic tools. Most of these tools are common in the industry. They are important for anyone who wants to be a data analyst. You do not need to know any programming language now to get started.

Your main set of tools will be:

• Microsoft Excel or Google Sheets can be used for data manipulation and simple analysis.

• SQL (Structured Query Language) helps you work with data in databases.

• Microsoft Power BI is good for data visualization and building interactive dashboards.

• A computer with a stable internet connection is needed.

You can learn these skills on your own, but it is much better if you follow a set plan. You can try platforms like SocialPrachar. The programs there match this path well. Experts there lead you through tools we picked, and you also practice a lot of SQL. They help you at every step when you make your own Power BI dashboard. This is a good option for anyone who wants to be a data analyst in Hyderabad. If you also take a strong generative ai course in hyderabad, it will help your skills get even better.

How to Set Up a Productive Learning Environment

A good way to learn is to make a good place for it. This is very important when you start your 90-day plan. The first thing you should do is make time for study every day. Try to give 2-3 hours for study time each day. It is better to read a little every day than try to do all your study at one time. Pick a time that works for you and try to keep that up.

After that, make sure your workspace is ready. This place can be at home or right on your computer. Try to stay away from things that take your attention away from work. Turn off notices that pop up on your phone and computer. Make sure you have everything you need. This can be Excel, a SQL client, and Power BI. When your space looks neat and clear, you can focus more and get things done.

At the end, try to join a group of people who want to learn with you. Being with others helps keep you on track and helps you when things get hard. A course like an ai developer course in Hyderabad lets you join study groups and find mentors who can help you. When you learn with other people this way, it makes the whole learning process better and more fun.

Step-by-Step Guide: Your 90-Day Data Analytics Roadmap

This 90-day study plan is split into three phases. Each phase takes 30 days. Every phase helps you build on what you learned in the last one. You will start by learning the main ideas about data. As you go on, you will learn more about data analysis and data visualization. This step-by-step study plan helps you use your time well. You will know what to do and will get ready for a job in this field.

You begin by making sure you have the basics down. Once you do that, you learn the main skills for working with data. In the last part of this study plan, you take what you know and use it to do real-world work. So, let’s look at each step in the study plan.

Step 1: Building Strong Foundations (Days 1–30: Excel, SQL Basics, Data Concepts)

The first month is focused on helping you build a good base. You will start to learn main ideas about data. You will also work with Microsoft Excel and feel more at ease using it. You will get started with the basics of SQL, a strong query language. The goal is for you to know how to work with, sort, and search through data.

You need to focus on how to use the things you learn. In Excel, practice data cleaning, sorting, and filtering. Try out the main things like VLOOKUP, INDEX-MATCH, and practice making pivot tables. With SQL, start by writing simple questions to get and filter data. This practice will help you feel good and sure about your skills.

Here is a sample weekly breakdown for your first 30 days:

Week	Focus Area	Key Topics to Cover
Week 1	Data Concepts & Excel Basics	What is data, structured vs. unstructured data, basic Excel formulas, sorting, and filtering.
Week 2	Advanced Excel Skills	Pivot Tables, VLOOKUP, INDEX-MATCH, conditional formatting, basic charts.
Week 3	Introduction to SQL	SELECT, FROM, WHERE clauses, basic data types, installing a SQL client.
Week 4	Basic SQL Queries	ORDER BY, GROUP BY, aggregate functions (SUM, AVG, COUNT), simple JOINs.

Step 2: Core Analytics Skills (Days 31–60: SQL Practice Plan, Data Cleaning, Power BI Fundamentals)

In your second month, you will get better at using technical skills. You will focus on advanced SQL, good data cleaning steps, and starting with data visualization in Power BI. This is when you work with raw data and turn it into something clear and easy to use. You also start to tell a story using your data.

Now, you should try to make your practice plan for SQL better. Work more on hard JOINs, write subqueries, and test out window functions. You will see that people get asked these things in job talks or when they do their daily work. To practice, you can find some data sets on the internet or go to websites that give SQL challenges.

You can start to use Power BI now. First, learn how to connect to data sources. Then, practice making simple changes in the Power Query Editor. The aim is to feel comfortable with the tool. You should know how to get your data ready for data visualization. A data science course in hyderabad can also help you practice with these analytic tools.

Step 3: Advanced Application & Job Readiness (Days 61–90: Data Analytics Projects, Power BI Dashboard Plan, Portfolio Building)

The last month is about bringing together all the things you know. You get ready for your job search during this time. You will work on complete data analytics projects. You will follow a power bi dashboard plan as well. You will make your own strong portfolio too. At this stage, you show companies that you can solve real business problems.

Pick two or three portfolio projects. These should show different skills. For example, you can do one project with exploratory data analysis using SQL and Excel. You can also do another project with an interactive dashboard made using power bi. Try to work with data sets about sales, customer churn, or marketing campaigns. This helps show how you use your business sense in each project.

Your power bi dashboard plan should be easy to follow and look nice. The power bi dashboard must show your insights in a way that people can read and use. For each project, try to use your data to tell a story. When you are done, write about how you created it and what you found out. This will help you build a great portfolio. You will also feel more sure in data science job interviews. You will be ready to start your path in data science.

Power BI is known for its use in data analytics and data analysis. You can use it to build a Power BI dashboard that will help with exploratory data analysis. This tool lets you find trends and look at data in new ways.

People who are interested in data science can use Power BI in their portfolio projects. If you want to stand out during your job search, showing how well you know data analytics and Power BI dashboard skills can help.

There is always a need for people who get data and can turn it into easy-to-understand ideas. Working on portfolio projects with Power BI and using data analytics makes your data analysis skills strong. This is good when you look for new jobs in data science and analytics.

Conclusion

To sum up, having a clear 90-day data analytics roadmap can help students, freshers, and those who want to change jobs. This plan will guide you from the basics of data analytics. First, you build your foundation. Next, you learn the main analytics skills. In the end, you go into more advanced practice. This way, you get a strong feel for data analytics and be ready for jobs in this area.

When you use tools like Excel, SQL, and Power BI, you make learning easier. If you get help from places like SocialPrachar, you will have the support and resources you need to do well. Remember, the journey to be a good data analyst is about more than learning new things. You also need to use what you learn on real projects. This helps you build a better portfolio. If you want to start a career in data analytics, you can book a free talk with our experts. They will help you find the best way to learn!

Frequently Asked Questions

Can I learn data analytics in 90 days?

Yes, you can get ready for a job in data analytics in just 90 days if you have a plan and work each day. You need to stay focused and take out some time every day. If you learn the skills that matter most and do real projects, you can pick up the basics for an entry-level job in big data.

data analytics roadmap 90 days

How should I practice SQL and Power BI within my 90 day study plan?

For SQL, take some time every day to practice. Stick to a plan. Be sure to work on problems at sites with real data. For Power BI, start by working on dashboards that are already done. This will help you know how they are made. After that, try to do your own data visualization projects. Use your skills and make something new from the start. Make your work look good and keep it simple for others to read.

Which data analytics projects are best for a beginner portfolio?

Beginner projects in data analysis help show that you can work with messy data and find useful facts. For example, you can try a sales data analysis to find out which products do well. You can also do a customer churn analysis to see why people leave. Another good idea is to build a marketing campaign dashboard, which helps with data visualization. These portfolio projects show you can use data to solve real problems and make things better for a business.

How does SocialPrachar support job readiness during this 90-day roadmap?

SocialPrachar helps you get ready for jobs with a clear study plan and help from experts. The leading ai training institute in hyderabad gives you practice with real projects, so you can get good at what you learn. They also offer practice with SQL and teach you how to use a Power BI dashboard. These things help you get real experience in power bi and data analyst work. You will feel sure of your skills and be ready to do well.

What is a realistic timeline to go from beginner to job-ready data analyst in 90 days?

Getting ready to work as a data analyst in just 90 days is hard, but you can do it if you stay focused. This is a short timeline for beginners:

Weeks 1–2: Foundations

• Learn the basics of statistics. This includes the mean, median, mode, and standard deviation.

• Take time to feel good with Excel or Google Sheets.

• Try making simple data visualizations.

Weeks 3–4: Programming Basics

• Start with Python (recommended) or R.

• Focus on things like variables, loops, conditionals, and functions.

• Practice working with data by using pandas in Python or dplyr in R.

Weeks 5–6: Data Cleaning & Exploration

• Take care of missing values, duplicates, and text issues.

• Look around the data, and show how things are spread.

Weeks 7–8: Advanced Analysis & Visualization

• Make advanced charts by using matplotlib, seaborn, or ggplot2.

• Learn about correlation and some basic stats that help you find more from your data.

• Work with real-world data that you can get from Kaggle or other places like it.

Weeks 9–10: SQL & Databases

• Learn the basics of SQL. Know how to use SELECT, JOIN, GROUP BY, and how to filter data.

• Connect databases to Python or R.

Weeks 11–12: Projects & Portfolio

• Do at least two full projects from start to end, like a sales analysis or customer segmentation.

• Write down your work in Jupyter Notebooks. Put your portfolio online.

n GitHub or a personal site

Which essential data analytics projects can I complete in 90 days to boost my resume?

You can make your resume better in 90 days by working on data analytics projects. Pick ones that show your technical skills, thinking, and how you help the business. Here are clear ideas you can try:

• Sales Data Analysis & Forecasting: Look at public sales data to find what brings in the most money. Use ARIMA or LSTM models to guess future sales. Show the results in Tableau or Power BI.

• Customer Segmentation: Run K-means clustering on retail or online shopping data. Share the main results in a dashboard.

• Churn Prediction Model: Use machine learning, like logistic regression or decision trees, to know which customers may leave. Point out the top reasons.

• Web Traffic Analytics: Check Google Analytics sample data to find user trends. Make the results clear with interactive visuals.

• Social Media Sentiment Analysis: Get data from Twitter with APIs. Use NLTK to read people’s feelings about the brand.

• Financial Data Visualization: Use Python tools like Plotly or Dash to build dashboards that show stock trends.

• A/B Testing Simulation: Set up an A/B test with fake data. Run t-tests and talk about what it means for business.

• Healthcare Data Analysis: Use open healthcare data to spot trends in illness or treatment. Make sure all data stays private and safe.

• Recommendation System Prototype: Make a simple recommendation system with either product or movie data.

Each of these projects lets you use power bi, machine learning, data analysis, and data visualization skills.

Finish these projects in 90 days to make your resume stronger.

What are recommended resources for building dashboards in Power BI during a 90-day data analytics plan?

When you build Power BI dashboards in your 90-day analytics plan, these are the best resources to use:

• Microsoft Learn – Power BI Learning Paths: You can find free and simple modules here for people new to this or even for those with some practice in Power BI.

• Power BI Community Forum: You can ask any questions, share your own tips, and work out problems you have with your power bi dashboard here.

• YouTube Channels (Guy in a Cube, Enterprise DNA): These channels show short how-to videos and long deep guides for who like to learn by watching.

• DAX Guide by SQLBI: A must-have site for DAX formulas with real examples that help you learn more about what you can do in Power BI.

• Udemy/Coursera Courses: You can take practice-based classes like “Mastering Power BI.” These let you learn about planning, making, showing, and sharing your work.

• Official Documentation: A big help for all things connected to the power bi dashboard. It goes over simple visuals and more safe ways to share.

• Templates & Sample Dashboards: You can use ready-made templates, or demo dashboards from AppSource or GitHub, and start working fast or get new ideas for your dashboard.

• Books: Books like “The Definitive Guide to DAX” (Ferrari & Russo) and “Supercharge Power BI” (Allington) are great if you want to go further and learn deep tricks.

• LinkedIn Learning – Power BI Dashboard Design Course: A course that shows how