What Exactly is Data Science?
Data science is an all-encompassing term that extends to the varied techniques of dealing with massive amounts of data by employing modern techniques and tools to detect patterns, extract valuable insights, and make business decisions. The technique of digging insights from the colossal amount of data entails bringing into play the complex algorithms of machine learning to develop predictive models and ranges of domains including statistical methodology, application domains, and computational science.
The field of Data Science treads on a lifecycle that consists of five stages, each with distinct tasks as discussed below:
Data Capture: This stage entails gathering data in its raw form by going through the process of acquiring, data entry, and extraction. Data Maintenance: This stage involves taking the raw data and converting it into a usable format which entails warehousing, cleansing, staging, processing, and architecture of data effectively.
Processing: The third stage implies assessing data for patterns, ranges, and biases to check for usability in terms of predictive analysis. This action calls for data mining, clustering, modeling, and summarizing data.
Analysis: The aggregated data is executed for analytics by employing exploratory, predictive and Qualitative analysis, regression, and Text mining. Communication: The whole process only becomes meaningful only when the collected results are meaningfully communicated through the use of graphs, charts, and reports. It involves data reporting, visualization, business intelligence, and the decision-making process.