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Data Science

Data science is the study of data to extract meaningful insights for business. It is a multidisciplinary approach that combines principles and practices from the fields of mathematics, statistics, artificial intelligence, and computer engineering to analyze large amounts of data.

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Topics to be covered


Introduction to Data Science


Data Collection and Cleaning


Data Exploration and Visualization


Data Manipulation and Analysis


Machine Learning Basics


Supervised Learning Algorithms


Unsupervised Learning Algorithms


Model Selection and Evaluation


Natural Language Processing (NLP)


Time Series Analysis

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Data Analyst Course Fees in Mumbai– A Comprehensive Guide For Beginners

Discover everything you need to know about data analyst course fees in Mumbai. This comprehensive guide covers costs, course details, and tips for beginners looking to start a career in data analysis.

DeveLearn Technologies

300 minutes

May 30, 2024

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Data Analyst Course Fees in Mumbai– A Comprehensive Guide For Beginners

Data Analytics Courses in Mumbai, India have gained significant popularity due to the transformative impact of data in today's world. This post explores various aspects of Data Analyst course, including fees, curriculum, duration, and the evolving role of data analytics.

In the last decade, data has become crucial for decision-making across industries. The vast volume of data, approximately 2.5 quintillion bytes globally daily, originates from diverse sources like emails, texts, social media platforms, and online media. This data explosion, fueled by e-commerce, banking, and digital media, has propelled the field of data analytics to new heights.

India, with the third-largest internet user base globally, is witnessing a surge in demand for data science professionals. Projections indicate that by 2025, around 85% of businesses in India will have adopted big data and analytics technologies. This growing adoption underscores the increasing significance of data analytics in the Indian business world.

What is Data Analytics?

Data Analytics involves utilizing tools, processes, and techniques to collect, organize, store, analyze, and manage data. Its main goal is to use statistical analysis and technology to uncover trends and solve problems. Through analytics, businesses can quickly respond to market shifts and gain a competitive advantage, ultimately aiming to improve overall corporate performance.

A Real-life Example of Data Analytics in Action

A tangible example of Data Analytics in action can be observed in Netflix's personalized viewing recommendations. This feature plays a pivotal role in Netflix's commercial success and involves a complex process of data analysis and algorithmic recommendations.

Netflix starts by collecting a wealth of data from its massive subscriber base of 163 million worldwide. This data includes viewership habits, device usage patterns, pause/resume actions, content ratings, and search queries.

Using sophisticated data analytics techniques, Netflix processes this vast amount of data to create detailed profiles for each viewer. These profiles capture significant trends and patterns in users' viewing behaviors.

The recommendation algorithm then kicks in, utilizing these profiles to generate personalized suggestions for each user. These suggestions are based on the algorithm's understanding of what content the user is likely to enjoy, considering factors like genre preferences, viewing history, and similar user behaviors.

This personalized approach significantly enhances the user experience, driving over 75% of viewing engagement, according to Netflix's reports. The success of this strategy is evident in Netflix's continued growth in revenue and user base, solidifying its position as a global leader in the streaming market.

Applications of Data Analytics

Here are some examples of how data analytics is applied across various industries:

  1. Retail: Data analytics helps retailers understand customer demands and buying patterns, allowing them to forecast trends, suggest new products, and expand their business.

  2. Healthcare: Healthcare organizations use patient data for accurate diagnoses and treatments. Data analytics also aids in developing innovative medication strategies.

  3. Manufacturing: Data analytics in manufacturing helps discover cost-saving methods, tackle supply chain challenges, address workforce shortages, and prevent equipment failures.

  4. Banking Sector: Financial institutions rely on analytics to identify potential loan defaults, predict customer attrition, and detect fraudulent transactions.

  5. Logistics: Logistics companies utilize data analytics to create new business models, optimize delivery routes, and ensure timely product deliveries.

Data Analysis vs Data Analytics

Data analysis refers to the process of examining, cleaning, transforming, and modeling data to discover useful information, conclusions, and insights. It involves tasks such as data cleaning, statistical analysis, data visualization, and hypothesis testing.

On the other hand, data analytics is a broader term that encompasses data analysis along with the methodologies, techniques, and tools used to perform data analysis effectively. It includes processes like data collection, data storage, data processing, data mining, machine learning, and predictive modeling, in addition to data analysis itself.

Business Analytics vs Data Analytics

Business analytics is a subset of data analytics that specifically focuses on utilizing data analysis techniques such as data mining, statistical analysis, predictive modeling, and other advanced analytics methods to extract actionable insights and support decision-making within business contexts.

While data analytics encompasses a broader range of activities related to data processing, management, and analysis across various domains, including business, healthcare, finance, etc., business analytics narrows its focus to the application of data analytics techniques within business operations and strategy. It aims to drive improvements in performance, efficiency, and decision-making processes by leveraging data-driven insights.

Data Analytics vs Data Science

Data analysts primarily focus on examining data to provide specific answers to predefined questions or queries. They often work with structured data and use tools like SQL, Excel, and visualization software to extract insights.

On the other hand, data scientists have a broader focus. They use advanced statistical techniques, machine learning algorithms, and programming languages like Python or R to explore data, uncover patterns, build predictive models, and generate actionable insights. Data science often involves working with both structured and unstructured data.

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Who is a Data Analyst?

A data analyst is a professional who plays a crucial role in an organization by bridging the gap between stakeholders and data.

Roles and responsibilities of a data analyst include:

  1. Using data visualization tools to oversee customer satisfaction surveys and report on outcomes.

  2. Identifying business needs, establishing success criteria, managing analytical projects, and evaluating outcomes.

  3. Monitoring procedures and systems to identify areas for improvement.

  4. Collaborating with stakeholders, technical teams, and support teams to define concepts, assess needs, and specify requirements.

  5. Converting inquiries into actionable analytical tasks.

  6. Gathering and organizing data from multiple sources to address client inquiries.

  7. Extracting insights using analytical techniques and tools, often through reports or dashboards.

  8. Transforming data into visualizations for easy understanding.

  9. Collaborating with data scientists to identify optimal solutions.

  10. Developing and maintaining backend code.

  11. Establishing data procedures and quality standards.

  12. Managing the codebase and recommending improvements.

  13. Designing tools for data validation.

  14. Collaborating within a team to analyze critical data for future business plans.

DeveLearn can provide information about data analyst course in Mumbai with prices and help individuals understand the roles and responsibilities of a data analyst.

Data Analytics Trends in Mumbai, India

Data analytics trends in India reflect the country's significant growth in the digital sphere. Over the past decade, the digital capacity has surged dramatically, creating a demand for skilled professionals in data analytics. India, being among the top 10 nations for big data analytics, hosts around 600 companies in this sector. The industry's current value of $2 billion is expected to soar to $16 billion by 2025, showcasing the immense potential and rapid expansion of data analytics in India.

Data Analytics Jobs in Mumbai, India

In Mumbai, India, the demand for data analytics professionals has surged significantly, outpacing the increase in the supply of professionals. There has been a remarkable 400% increase in demand, while the supply has only grown by 19%. Around 21% of analytics positions in India are open to recent graduates, offering opportunities for entry into the field.

Key employers in Mumbai and across India include renowned companies such as Tech Mahindra, TCS, Genpact, Wipro, and HCL Infosystems, among others. Mumbai, along with Bengaluru and Gurgaon, is a key location for data analytics jobs, with a significant share of the 97,000 open positions in India concentrated in these cities.

India's prominence in the global data analytics job market is evident, accounting for over 6% of all global job postings in this field. With the projected adoption of big data and analytics technology by 85% of businesses by 2022, the demand for data analytics professionals is expected to continue growing. By 2025, India is anticipated to hold a 32% share of the global data analytics market, further emphasizing the country's importance in this domain.

Various Profiles of Data Analysts

  1. IT Systems Analysts: These professionals specialize in developing solutions for information technology-related issues, ensuring smooth functioning and efficiency in IT systems.

  2. Healthcare Data Analysts: Focused on the healthcare industry, these analysts support researchers and clinicians by leveraging data analytics to solve healthcare challenges and improve patient outcomes.

  3. Operations Analysts: Working in large corporations, operations analysts concentrate on internal operations such as reporting systems, product manufacturing processes, and distribution logistics, aiming to enhance operational efficiency.

  4. Data Scientists: Data scientists are experts in gathering, analyzing, and interpreting data using advanced analytics tools, programming languages, and data visualization techniques. They play a crucial role in deriving valuable insights from data.

  5. Data Engineers: Data engineers are responsible for designing and optimizing the infrastructure that supports data analytics operations, especially concerning large and complex datasets. They focus on data storage, processing, and integration.

  6. Data Analytics Consultants: Consultants in data analytics work with companies to provide actionable insights that improve business efficiency. They often work on projects with defined timelines, assisting multiple companies in achieving their data-driven goals.

Data Analytics Courses in Mumbai, India

Fresh graduates often find it hard to get a job right after completing their degrees. This problem usually happens because they don't have enough real-world experience during their studies. While schools teach important theories, they might not always provide practical skills needed for jobs. To bridge this gap, many organizations and online platforms in Mumbai, India offer data analyst course in Mumbai with placement support.

People looking to start their own businesses or enter the data analytics field take these courses. These programs teach students how to understand consumer behavior from large sets of data. Those wanting to become data scientists or analysts usually pursue degrees like B.Tech in Computer Science, M.Sc in Data Analytics, or M.Sc in Computer Science with a focus on data analytics and data science. A bachelor's degree, which takes about 3-4 years to complete, is generally enough for entry-level data analyst jobs.

Additionally, individuals can take online & offline data analytics course in Mumbai with DeveLearn to learn basic concepts. They can also earn globally recognized certifications that cover key tools and programming languages used in data analysis, such as Big Data, Python, and Machine Learning.

Data Analytics Course Fees in Mumbai, India

The cost of data analytics courses can vary based on the type and level of the program:

  • Certification Level Data Analytics Courses: INR 10,000 – 1,00,000

  • Diploma Level Data Analytics Courses: INR 50,000 – 2,00,000

  • Undergraduate Level Data Analytics Courses: INR 90,000 – 21,00,000

  • Postgraduate Level Data Analytics Courses: INR 20,000 – 23,00,000

Data Analytics Course Fees: Online vs. Offline

The cost of data analytics courses often depends on factors like duration, unique features, and post-course support. Both online and offline data analyst institutes in Mumbai provide high-quality training, so the curriculum is usually not the only reason for the variation in fees.

Factors that can influence the difference in fees between online and offline courses include practical projects, access to learning portals, notes, slides, and other study materials. These additional resources can significantly impact the overall cost.

To learn more about data analytics course in Mumbai and their associated fees, connect with the DeveLearn expert team today!