Data Analysis

 What is data analysis?

Data analysis is the process of examining, cleaning, transforming, and modeling data to extract useful information, draw conclusions, and support decision-making. It involves using statistical, computational, and visualization techniques to identify patterns, trends, and insights within large sets of data. Data analysis can be applied to various fields, such as business, healthcare, finance, and social sciences, to inform strategic planning, improve operations, and drive innovation.

Data analytics

Data analytics is the process of analyzing and interpreting large sets of data to uncover patterns, trends, and insights that can inform decision-making and strategy. This process involves collecting, cleaning, and organizing data, as well as using statistical and computational methods to analyze the data and extract meaningful information. Data analytics can be applied in a variety of fields, including business, healthcare, finance, and government, to inform decision-making and improve performance.

Complete roadmap for become data analytics

1. Start with the basics: Familiarize yourself with the basics of data analytics by studying statistics, probability, and programming languages such as Python or R.

2. Learn data visualization: Learn how to use data visualization tools such as Tableau, Power BI, or Excel to create compelling visualizations that can help you understand and communicate data insights.

3. Study data mining and machine learning: Learn the basics of data mining and machine learning, including supervised and unsupervised learning, and gain experience with popular machine learning libraries such as scikit-learn or TensorFlow.

4. Learn data wrangling and cleaning: Learn how to clean and manipulate data using tools such as pandas, numpy, and SQL.

5. Explore big data technologies: Learn about big data technologies such as Hadoop, Spark, and Hive to gain experience working with large datasets.

6. Build a portfolio: Build a portfolio of data analytics projects that demonstrate your skills and knowledge.

7. Get certified: Consider getting certified in data analytics or machine learning to demonstrate your expertise to potential employers.

8. Network: Join data analytics communities, attend conferences, and network with other data analysts to stay up-to-date with the latest trends and technologies.

9. Keep learning: Stay current with the latest trends and technologies by continuing your education through online courses, workshops, and bootcamps.

10. Seek employment: Apply for data analytics roles at companies in your desired field and continue to grow your skills and knowledge through on-the-job experience.

data analytics salary in different countries

top-paying countries around the world include:

• Average annual data analyst salary in India: Over ₹9,50,000
• Average annual data analyst salary in USA: Over $65,000
• Average annual data analyst salary in United Kingdom: Over £27000
• Average annual data analyst salary in Canada: Over C$56000
• Average annual data analyst salary in Australia: A$82K 
• Average annual data analyst salary in Singapore: S$55K
• Average annual data analyst salary in Germany: €45,338
• Average annual data analyst salary in Denmark: DKK 881,794
• Average annual data analyst salary in Malaysia: RM 44127