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Data science is devoted to the extraction of clean information from raw data to form actionable insights. It is used for prediction and decision making.

Structured Data:

The data which is to the point, factual, and highly organized is referred to as structured data. It is quantitative in nature, i.e., it is related to quantities that means it contains measurable numerical values like numbers, dates, and times.

Unstructured Data:

All the unstructured files, log files, audio files, and image files are included in the unstructured data. Some organizations have much data available, but they did not know how to derive data value since the data is raw.

WHAT IS DATA SCIENCE?

Data science is the process of using tools and techniques to draw actionable information out of huge volumes of noisy data. Data science is used for everything from business decision making to sports analytics to insurance risk assessment.

How Does Data Science Work?

Data science involves several disciplines to produce a holistic, thorough and refined look into raw data. While some data scientists specialize in narrow areas of the field, others are generalists and have skills spanning everything from data engineering, math, statistics, advanced computing and visualizations, and are able to effectively sift through muddled masses of information and communicate only the most vital bits that will help drive innovation and efficiency.

Data scientists often rely heavily on artificial intelligence, especially its subfields of machine learning and deep learning, to create models and make predictions using algorithms and other techniques.

Data science can be thought of as having a five-stage life cycle:

Data acquisition: To collect data

Data transformation:To remove unwanted data

Data analysis: Analysing of collected data

Data modeling: To create multiple modeling using machine learning and scientific methods

Data visualization: Choose best model and visualization to client