Data Analyst Course Fees In India – A Comprehensive Guide For Beginners
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In this post, we'll explore various aspects of Data Analytics Courses in India, Data Analytics Course fees, curriculum, duration, and more.
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What is Data Analytics? A Real-life Example of Data Analytics in Action Applications of Data Analytics Data Analysis vs Data Analytics Business Analytics vs Data Analytics Data Analytics vs Data Science Who is a Data Analyst? Data Analytics Trends in India Data Analytics Jobs in India Various Profiles of Data Analysts: Data Analytics Courses in India Data Analytics Course Fees: Data Analytics Course Fees: Online vs. Offline
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Over the last decade, data has transformed how we see the world. The massive amount of data generated daily, around 2.5 quintillion bytes globally, comes from emails, texts, YouTube, and more. This explosion of data from e-commerce, banking, social media, and online media has greatly expanded the field of data analytics.
With India having the third-largest internet user base, the demand for data science is growing. By 2022, it's expected that 85% of businesses will have adopted big data and analytics technology.
What is Data Analytics?
Data Analytics encompasses the tools, processes, and techniques for gathering, organizing, storing, analyzing, and managing data. Its primary objective is to apply statistical analysis and technology to identify trends and address issues. By leveraging analytics, businesses can swiftly adapt to market changes and gain a competitive edge. Ultimately, Data Analytics aims to enhance corporate performance.
A Real-life Example of Data Analytics in Action
A prime illustration of Data Analytics at work is seen in Netflix's personalized viewing suggestions. How does this feature contribute to Netflix's commercial success, and how does the platform generate these recommendations?
It all begins with data collection, where Netflix gathers diverse information from its 163 million global subscribers. This includes viewership patterns, device usage, pause/resume activities, content ratings, and search queries.
Through data analytics, Netflix synthesizes this data to create detailed viewer profiles. The recommendation algorithm then generates personalized suggestions based on significant trends and patterns in each user's viewing behavior.
This personalized approach significantly enhances the user experience, with personalized recommendations driving over 75% of viewing engagement, as reported by Netflix. This strategy has propelled Netflix's dominance in the global streaming market, reflected in its continuous growth in revenue and user base.
Applications of Data Analytics
- Retail: Data analytics empowers retailers to understand customer demands and purchasing patterns, enabling them to forecast trends, recommend new products, and expand their business.
- Healthcare: Healthcare organizations utilize patient data to deliver potentially life-saving diagnoses and treatments. Data analytics also facilitates the development of innovative medication strategies.
- Manufacturing: Through data analytics, the manufacturing sector discovers innovative cost-saving methods. It helps address complex supply chain issues, workforce shortages, and equipment failures.
- Banking Sector: Financial institutions leverage analytics to identify potential loan defaulters and predict customer attrition rates. Additionally, it assists in detecting fraudulent transactions.
- Logistics: Logistics companies utilize data analytics to devise new business models and optimize routes, ensuring timely delivery of goods.
Data Analysis vs Data Analytics
Although "data analytics" and "data analysis" are sometimes used interchangeably, data analysis is a subset of "data analytics" focused on examining, modifying, modeling, and deriving meaning from data. Data analytics encompasses data analysis as well as the procedures and tools required to execute it.
Business Analytics vs Data Analytics
Data analytics also encompasses business analytics, which employs techniques such as data mining, statistical analysis, and predictive modeling from data analytics to aid businesses in making informed decisions.
Data Analytics vs Data Science
Data scientists typically focus on generating broad insights, while data analysts concentrate on providing answers to specific queries.
Data science utilizes data to forecast and/or understand the future, while data analytics describes the current or past state of reality.
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