This content originally appeared on DEV Community and was authored by Philemonkipkirui
Data Science is a field that is concerned with uncovering actionable insights from data. This is done through the combination of mathematics, statistics, programming, advanced analytics , artificial intelligence and machine learning.
The life cycle of data science encompasses of Data Ingestion. It Involves collection of raw data either structured or unstructured from various sources.
Data storage and processing. Depending on the format or nature of data, specific storage factors are considered. This stage also involves the cleaning, duplication, transformation and combining of data.
Data analysis. This involves the examining of data to identify patterns, biases, ranges and distributions within data.
Communication. This is the last stage of data analysis where meaningful insights have been obtained. Such insights allow for reasonable decision making.
Education on data science is mostly provided in institutions of higher learning as either independent majors or complements of majors such as economics, statistics and even engineering. Courses on such are also offered by private entities whose objectives align with proficiency in data analysis and manipulation.
The tools commonly used for data science are mostly programming languages with prebuilt statistical modelling, machine learning and graphical capabilities. Some of the common tools are R Studio, Python with its numerous libraries such as Numpy, Pandas and Matplotlib.
This content originally appeared on DEV Community and was authored by Philemonkipkirui
Philemonkipkirui | Sciencx (2024-08-11T19:07:36+00:00) Data Science. Retrieved from https://www.scien.cx/2024/08/11/data-science-3/
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