Business analytics is the practice of iterative, methodical exploration of an organization’s data, with an emphasis on statistical analysis. Business analytics is used by companies committed to data-driven decision-making. It is about using your data to derive information, insights, knowledge, and recommendations. Businesses use business analytics to improve effectiveness and efficiency of their solutions.
Analytics has progressed from simple descriptive analytics to being predictive and prescriptive. Multiple components of big data analysis include data mining, machine learning, web mining, natural language processing, social network analysis, and visualization.
Python and R are the two most popular programming languages for data scientists as of now. Latest Popularity chart can be viewed here.
Python is an interpreted high-level programming language for general-purpose programming. Created by Guido van Rossum and first released in 1991, Python has a design philosophy that emphasizes code readability, notably using significant whitespace. Python is open source, has awesome community support, is easy to learn, good for quick scripting as well as coding for actual deployments, good for web coding too.
Start with basics of the Python language. In detail understanding of topics like control flow, input output, data structures, functions, regular expressions and object orientation in Python. Popular Python libraries like NumPy, Pandas, SciPy, Matplotlib, Scikit-Learn and NLTK comes next.
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Business analytics is the practice of iterative, methodical exploration of an organization's data, with an emphasis on statistical analysis.