The process of analytics begins with defining business problem. During this step, questions are asked from business stakeholders and business problems of stakeholders are understood and documented.
Data Acquisition step in Data Analytics process step
Data Acquisition step is used to collect data from various sources for analysis to answer the question raised in Business Definition Step.
Data Acquisition step involves
- File Handling
- Web Scraping
- SQL Data
Some examples of Data Acquisition steps are :
- Twitter, Facebook, LinkedIn, and other social media and information sites provide streaming APIs.
- Server logs can be extracted from enterprise system servers to analyze and optimize application performance.
- Both R and Python are open-source programming languages.
- New libraries and tools are continuously added to both R and Python.
- Most of the tasks that can be performed through R can also be done using Python.
- R language is mainly used for statistical analysis whereas Python provides a more general approach to data science.
- R is a language specifically built by statisticians and is better for analytical tasks.
- Another difference between R and other languages is the array of outputs and visuals available for data analysis.
Data Science is also known as data driven data science. It is an interdisciplinary field of scientific methods, processes, algorithms and systems to extract knowledge or insights from data in various forms ( either structured or unstructured data )