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Today's Technology-Data Science
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A future career in Data Science will be more promising. How?
- Data accumulation usually is done by database management (SQL), retrieving semi-structured data, and then categorically storing them using Hadoop, Apache Flink, etc.
- Data cleaning to remove the inconsistencies and anomalies using tools like Python, R, SAS, Hadoop, etc.
- Data analysis to understand the data, find patterns that can be useful, details which can solve a particular problem using Python libraries and R libraries, statistical modeling, experimental designing, etc.
- Data modeling by putting in various objectives and cases and try to get an algorithm for the business need by using machine learning.
- Data interpreting by making non-tech people understand what you have discovered from the data so that one can have an insight using data visualization tools and most importantly communication and presentation skills.