Over the past decade, data has transformed how we see the world. Every day, around 2.5 quintillion bytes of data are generated globally—from emails, text messages, and YouTube videos to e-commerce transactions, online banking, insurance records, and social media interactions. With the rise of digital platforms and businesses shifting online, data analytics has become more important than ever.
India, with the third-largest internet user base in the world, has witnessed rapid growth in data science and analytics. According to a 2018 report by the World Economic Forum (WEF), 85% of businesses were expected to adopt big data and analytics technologies by the end of 2022. This shows how essential data analytics skills are in today’s job market.
If you're looking to build a career in this field, Uncodemy offers comprehensive Data Analytics courses designed to equip you with industry-relevant skills. In this article, we’ll take a detailed look at Uncodemy’s Data Analytics courses, including course fees, curriculum, duration, and more.
🚀 The Future is Data! Are You Ready?
By 2025, India will command 32% of the global data analytics market, solidifying its position as a powerhouse in the field. With over 6% of global job postings dedicated to data analytics, the demand for skilled professionals is skyrocketing!
🔹 Why Choose Data Analytics?
✅ High-paying career opportunities
✅ Massive demand across industries
✅ Future-proof skillset
🌟 Join Uncodemy & Secure Your Future! 🌟
📌 Course Fee: ₹20,000/-
🔹 Non-refundable Upfront Fee (One-time payment to secure your seat)
🔹 + GST (18% as per government regulations)
🚀 Don't just learn—master data analytics with industry experts!
🔗 Enroll now and take the first step toward a lucrative career!
What is Data Analytics?
Data Analytics is all about collecting, organizing, storing, and analyzing data to find patterns and solve problems. It involves using statistical techniques and technology to make sense of data, helping businesses make better decisions. With the right data insights, companies can quickly respond to market trends and stay ahead of competitors. In simple terms, the goal of Data Analytics is to improve business performance by making smarter, data-driven decisions.
Real-Life Example of Data Analytics in Action
A great example of Data Analytics in everyday life is how Netflix suggests movies and shows based on your preferences. But have you ever wondered how Netflix figures out what you might like to watch next?
It all starts with data collection. Netflix gathers information from its 163 million users worldwide—what they watch, when they watch, which device they use, whether they pause or skip scenes, how they rate content, and even what they search for.
Using Data Analytics, Netflix connects all these details to create a detailed viewing profile for each user. Their recommendation system then analyzes patterns and trends to suggest content that matches individual preferences. .
This personalized experience has a big impact—Netflix reports that over 75% of its watch time comes from recommendations. As a result, Netflix continues to dominate the global streaming industry, growing year after year, all thanks to the power of Data Analytics.
How Uncodemy Helps You Learn Data Analytics
At Uncodemy, we teach you how to use Data Analytics in real-world scenarios just like this. Our course covers everything from data collection and storage to analysis and visualization. Whether you’re a beginner or looking to advance your skills, Uncodemy’s Data Analytics course gives you hands-on training to build a strong career in this high-demand field.
Applications of Data Analytics
Data Analytics is widely used across various industries to improve decision-making and business operations. Let’s explore some key sectors where Data Analytics plays a crucial role:
Retail: Retailers use Data Analytics to understand customer preferences, buying habits, and market trends. This helps them recommend products, predict future demand, and grow their business effectively.
2. Healthcare: In the healthcare industry, Data Analytics helps doctors and researchers analyze patient data for better diagnoses and treatments. It also plays a key role in developing new medicines and improving healthcare strategies.
3. Manufacturing: Manufacturing companies use Data Analytics to reduce costs, improve efficiency, and solve supply chain challenges. It helps in preventing equipment failures, managing workforce shortages, and optimizing production processes.
4. Banking & Finance:Banks and financial institutions use analytics to detect fraud, assess loan risks, and understand customer behavior. It also helps them predict which customers might stop using their services and take steps to retain them.
5. Logistics:Logistics companies rely on Data Analytics to plan better delivery routes, track shipments, and improve overall supply chain efficiency. This ensures timely deliveries and enhances customer satisfaction.
How Uncodemy Prepares You for These Industries :
At Uncodemy, our Data Analytics course is designed to equip you with real-world skills that are highly valued in these industries. Whether it’s retail, healthcare, banking, or logistics, our training covers industry-specific use cases, hands-on projects, and practical applications to help you build a successful career in Data Analytics.
Data Analysis vs. Data Analytics
Many people use the terms "Data Analysis" and "Data Analytics" interchangeably, but they are slightly different. Data Analysis is a part of Data Analytics that focuses on examining, organizing, and interpreting data to find useful insights. On the other hand, Data Analytics includes not just analysis but also the tools, techniques, and processes used to work with data.
Business Analytics vs. Data Analytics
Business Analytics is a branch of Data Analytics that focuses on helping businesses make informed decisions. It uses techniques like data mining, statistical analysis, and predictive modeling to identify trends and optimize business strategies. In simple terms, while Data Analytics is broad and applies to various fields, Business Analytics is specifically aimed at improving business performance.
Data Analytics vs. Data Science
The key difference between Data Analytics and Data Science is their purpose. Data Analysts work with existing data to answer specific questions and solve problems. In contrast, Data Scientists focus on finding deeper insights, building machine learning models, and predicting future trends.
In simple words, Data Analytics helps businesses understand what has happened and what is currently happening, while Data Science goes a step further to predict what might happen in the future.
How Uncodemy Helps You Learn These Concepts
At Uncodemy, our Data Analytics course covers everything from data analysis techniques to predictive modeling and business analytics. We ensure you gain hands-on experience in working with data and understanding real-world applications. Whether you’re interested in business intelligence, reporting, or deeper data insights, our course prepares you for all aspects of Data Analytics.
Who is a Data Analyst?
A Data Analyst plays a crucial role in helping businesses make informed decisions. They act as the bridge between raw data and business strategy, ensuring that stakeholders can understand and use data effectively.
Here are some key responsibilities of a Data Analyst:
- Use data visualization tools to create reports and dashboards that track customer satisfaction and business performance.
- Work closely with different teams to understand business needs, define project goals, and analyze results.
- Monitor processes and systems to find areas for improvement and optimization.
- Collaborate with business leaders, technical teams, and stakeholders to identify key requirements and data-driven solutions.
- Convert complex business questions into structured analytical tasks.
- Collect, clean, and organize data from various sources to ensure accuracy and relevance.
- Apply analytical techniques to extract valuable insights and present findings through reports or interactive dashboards.
- Develop and maintain data pipelines, ensuring smooth data processing and storage.
- Work alongside data scientists to identify and implement the best solutions for business challenges.
- Ensure data quality by implementing validation processes and refining data collection methods.
- Continuously improve data models, reporting structures, and backend code to enhance efficiency.
Data Analytics Trends in India
The rapid growth of digital technology has transformed industries worldwide. In 1995, the total digital data was around 140 billion gigabytes. By 2020, this number had exploded to 50 trillion gigabytes—showing the massive demand for data professionals.
India is one of the top 10 countries for Big Data Analytics, with over 600 companies specializing in this field. The Indian Big Data Analytics industry is currently valued at $2 billion and is projected to grow to $16 billion by 2025. With businesses increasingly relying on data, there is a growing demand for skilled Data Analysts in India.
How Uncodemy Prepares You for This Industry
At Uncodemy, our Data Analytics course is designed to equip you with the skills needed to succeed in this fast-growing industry. We provide hands-on training in data analysis, visualization, business intelligence, and real-world applications to help you secure a high-demand job in Big Data and Analytics.
Data Analytics Jobs at Uncodemy
The demand for data analytics professionals is skyrocketing! While the number of skilled professionals in India has grown by only 19%, the demand has shot up by 400%. This means huge opportunities for aspiring analysts. Around 21% of analytics job roles in India are open to fresh graduates. Top recruiters include companies like Tech Mahindra, TCS, Genpact, Wipro, and HCL Infosystems.
Currently, India contributes to over 6% of global job postings in data analytics. A report by the World Economic Forum (WEF) predicted that by the end of 2022, 85% of businesses would have adopted big data and analytics technologies. By 2025, India is expected to hold a 32% share in the global data analytics market. Right now, there are around 97,000 open data analytics jobs in India, with 24% of them based in Bengaluru. Mumbai and Delhi NCR (Noida, Delhi, Gurgaon) are also major hiring hubs.
Job Roles You Can Get After Learning Data Analytics from Uncodemy
After completing Uncodemy’s Data Analytics course, you can work in various roles such as:
- IT Systems Analyst – Works on developing solutions to improve IT processes and solve tech-related challenges.
- Healthcare Data Analyst – Plays a key role in improving patient care by analyzing medical data, helping doctors and researchers make better decisions.
- Operations Analyst – Focuses on optimizing business operations like reporting systems, product manufacturing, and supply chain management.
- Data Scientist – Specializes in collecting and analyzing complex data, using advanced tools and programming languages to gain valuable insights.
- Data Engineer – – Builds and optimizes data infrastructure, ensuring businesses can handle and process large amounts of data efficiently.
- Data Analytics Consultant – Works with multiple companies to provide data-driven strategies for improving business efficiency.
Average Salary After Completing a Data Analytics Course at Uncodemy?
As a beginner in data analytics, you can expect a salary between ₹3 to ₹4 LPA. With 5 to 9 years of experience, your salary can go up to ₹6 LPA. The highest-paying positions, such as Data Scientist or Data Science Engineer, typically offer salaries between ₹6 to ₹8 LPA.
Uncodemy ensures that students get hands-on training, real-world projects, and placement assistance to land top jobs in the industry. If you want to start your journey in data analytics, now is the time to upskill!
Data Analytics Course at Uncodemy
Many students struggle to find a job immediately after completing their undergraduate or postgraduate studies. One major reason is the lack of real-world industry exposure. While college courses focus on theoretical knowledge, they often don’t provide practical experience or insights into the skills companies look for. To bridge this gap, various institutes and online platforms in India, including Uncodemy, offer specialized Data Analytics training with job assistance.
These courses are ideal for those who want to build a strong career in data analytics or even start their own business. Learning data analytics helps professionals understand consumer behavior by analyzing large datasets. Students who wish to work as data analysts or data scientists can pursue different learning paths, such as a B.Tech in Computer Science, an M.Sc in Data Analytics, or an M.Sc in Computer Science with a specialization in data analytics and data science. However, to land a data analyst job, a bachelor’s degree (which takes about 3–4 years) is the minimum requirement.
For beginners, online courses provide a great way to learn the fundamentals. Instead of expensive degree programs, students can opt for practical, industry-focused Data Analytics training at Uncodemy, which covers all essential tools and programming languages such as Big Data, Python, SQL, and Machine Learning. Uncodemy also provides hands-on projects and certification, helping students gain globally recognized credentials.
Data Analytics Course Fees at Uncodemy:
The cost of a Data Analytics course depends on the type of program. Certificate courses are more affordable, while postgraduate degrees tend to be more expensive. Below is a general fee structure:
- Certificate Courses in Data Analytics – ₹500 to ₹10,000
- Diploma in Data Analytics – ₹9,300 to ₹2,00,000
- Undergraduate Degree (B.Tech, B.Sc, etc.) – ₹90,000 to ₹21,00,000
- Postgraduate Degree (M.Tech, M.Sc, MBA, etc.) – ₹20,000 to ₹23,00,000
At Uncodemy, we focus on making high-quality Data Analytics training affordable and job-oriented. Our courses are designed to provide practical exposure, live projects, and placement support to help students kick-start their careers in data analytics.
Data Analytics Course Fees: Online vs Offline at Uncodemy
The course fee for Data Analytics training varies based on course duration, features, and post-course support. Both online and offline institutes offer quality training, so the syllabus itself is usually not the main reason for fee differences. However, factors like hands-on projects, access to study materials, live sessions, and placement support play a key role in determining course costs.
Best Data Analytics Courses at Uncodemy
Let’s divide Data Analytics courses into three broad categories –Certification, Diploma, and Advanced Programs:
Certification Courses:-
- Data Analytics with Python – Uncodemy – Course Fee: ₹25,000
- Data Analytics for Beginners – Uncodemy –Course Fee: ₹20,000
- Power BI and SQL for Data Analytics – Uncodemy – Course Fee: ₹25,000
Diploma Courses:-
- Diploma in Data Analytics – Uncodemy – Course Fee:₹30,000
- Post Graduate Diploma in Business Analytics – Uncodemy – Course Fee:₹1,00,000
- Advanced Data Analytics Program (Big Data & AI) – Uncodemy – Course Fee:₹120000
Advanced Programs:-
- Data Analytics & Business Intelligence – Uncodemy – Course Fee: ₹1,50,000
- AI-Powered Data Analytics – Uncodemy – Course Fee: ₹90,000
- Full-Stack Data Science & Analytics – Uncodemy – Course Fee: ₹1,10,000
Modules Covered in the Data Analytics Course at Uncodemy
The Data Analytics course at Uncodemy is designed to provide students with hands-on experience in working with real-world data. The course covers essential topics, including:
- Data Structures and Algorithms
- Business Fundamentals
- Data Visualization
- Simulation
- Marketing Analytics
- Retail Analytics
- Probability and Statistics
- Text Analytics
- Supply Chain Analytics
- Statistical Analysis
- Machine Learning
- Pricing Analytics
- Customer Analytics
- Relational Database Management Systems (RDBMS)
- Data Collection
- Forecasting Analytics
- Optimization
- Social Network Analytics
Tools Used in the Data Analytics Course at Uncodemy
To efficiently process, manipulate, and analyze data, various tools and technologies are used in data analytics. Some of the top tools covered in the Uncodemy Data Analytics course include:
- Excel for Business Analytics-Excel is one of the most widely used tools in data analytics. It offers features like pivot tables, formulas, and data visualization that help in sorting, analyzing, and presenting data effectively.
- Python-Python is an essential programming language for data analysts. It is easy to learn, widely used in the industry, and has numerous libraries like Pandas, NumPy, and Matplotlib that simplify data analysis.
- R programming-R is another powerful tool for statistical computing and data visualization. It is commonly used for handling large datasets and performing complex statistical analysis.
- Jupyter Notebook-Jupyter Notebook is an open-source tool that allows users to write and execute code interactively. It supports multiple languages like Python and R, making it ideal for data analysis and visualization.
- Apache Spark-Apache Spark is a big data processing framework that helps in analyzing large datasets at high speed. It is used in machine learning and real-time data processing applications.
- SAS (Statistical Analysis System)-SAS is a popular commercial software used for predictive analytics, business intelligence, and data mining. It is commonly used by enterprises to handle large-scale data processing.
- Microsoft Power BI-Power BI is a business intelligence tool that allows users to create interactive dashboards and reports. It integrates well with Excel, SQL, and other data sources, making it one of the most preferred tools for data analytics.
- Tableau-Tableau is widely used for data visualization. It provides a drag-and-drop interface, allowing users to create powerful dashboards and charts without writing complex code.
- KNIME-KNIME is a data integration and machine learning platform that allows users to combine data from multiple sources and perform advanced analytics.
- QlikView-QlikView is a business intelligence and data visualization tool that helps businesses analyze data and generate insights quickly.
- RapidMiner-RapidMiner is a machine learning and data analytics platform that provides easy-to-use tools for data preparation, modeling, and visualization.
- Splunk-Splunk is widely used for analyzing machine-generated data from applications, networks, and websites. It is commonly used in IT and cybersecurity analytics.
Prerequisites for Enrolling in the Data Analytics Course at Uncodemy
There are no strict prerequisites for joining this course. However, having the following skills can be beneficial:
- Analytical skills – The ability to understand and interpret data effectively.
- Problem-solving and critical thinking – Essential for identifying trends and insights in data.
- Communication skills – Helpful in presenting and explaining data-driven insights clearly.
FAQs
1. Are Data Analytics courses at Uncodemy held online or offline?
Uncodemy provides both online and offline Data Analytics courses, making it flexible for learners. The online courses allow students to learn from anywhere, while offline batches offer in-person learning experiences.
Many global platforms like Coursera, Udemy, edX, and SimpliLearn also offer data analytics courses, but Uncodemy provides industry-relevant, job-oriented training with live projects and hands-on practice.
Depending on the course structure, the duration may range from a few months to a maximum of two years, similar to programs offered by reputed institutes like IIMs and other business schools.
2. Can I learn Big Data Analytics without any coding experience?
Yes! You don’t need advanced coding skills to start learning Big Data Analytics. While programming knowledge can be helpful, many open-source tools allow analysts to study and examine data without writing complex codes.
At Uncodemy, the course focuses on practical learning, covering key areas like data visualization, analytics, and data management tools, making it easier for non-coders to transition into the field of data analytics.
3. How long does it take to become a Data Analyst after completing a course at Uncodemy?
If you actively learn and practice, you can become a Data Analyst in 3 to 6 months with Uncodemy’s training.
- A bachelor’s degree takes 3-4 years, and a master’s degree takes 2 years.
- A Diploma or PG Diploma in data analytics typically lasts between 8 months to 1 year.
- Uncodemy’s courses are skill-based and fast-tracked, so you can enter the job market much sooner than with a traditional degree.
Conclusion
With 96% of companies hiring Data Analysts, there is a huge demand for skilled professionals. By 2025, the global data analytics market is expected to surpass $20 billion, making this a high-growth career.
Take advantage of this digital revolution and enroll in Uncodemy’s Data Analytics course to secure a high-paying job in this field.
