Data Science is an interdisciplinary field about processes and systems to extract knowledge or insights from data in various forms, either structured or unstructured, which is a continuation of some of the data analysis fields such as statistics, data mining, and predictive analytics, similar to Knowledge Discovery in Databases (KDD). [Click here for reference]
However, the definition of data science is still evolving.
“This hot new field promises to revolutionize industries from business to government, health care to academia”
– The New York Times
Who are the Data Scientists?
There are myths/misconceptions about data scientists. Many claim themselves as data scientists even though they are not. To be a data scientist one must possess deep understanding and/or must be hands-on with all of the following skills:
- Data collection
- Data cleaning and data supervision
- Data Warehousing
- Data Analysis
- Machine Learning
- Coding (at least one coding language. R and Python are among the few most popular Languages)
- Data Visualization
- Business scopes/challenges
- Troubleshooting and
- Pattern Recognition
Big data is another popular stream of data science. Knowledge of big data is like preparing for the future. However, one does not need to know Big Data to be successful as a data scientist.
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