Data
Science is a process of extracting knowledge from data. Data science is
emerging to meet the challenges of processing large data sets which
require versatile skill set and specialized in specific domain. Data scientist
analyse the complex problems and ensure rich consistency of data sets with
creating visualizations to aid in understanding data.
Data science is,
in general terms, the extraction
of knowledge from data. The key word in this job title is
"science," with the main goals being to extract meaning from data and
to produce data products. It employs techniques and theories drawn from many
fields within the broad areas of mathematics, statistics, and information
technology, including signal processing, statistical
learning, computer programming, data engineering, pattern
recognition and learning, visualization, uncertainty modeling, data
warehousing, and high performance computing. The discipline is not
restricted only to so-called big data, although an important aspect of data
science is its ability to easily cope with large amounts of data. The
development of machine learning, a branch of artificial
intelligence used to uncover patterns in data from which practical and usable
predictive models can be developed, has enhanced the growth and importance of
data science.
A
practitioner of data science is known as a data scientist. Data scientists
investigate complex problems through expertise in disciplines within the fields
of mathematics, statistics, and computer science. These areas represent great
breadth and diversity of knowledge, and a data scientist will most likely be
expert in only one or at most two of these areas and merely proficient in the
other. Therefore a data scientist typically works as part of a team whose other
members have knowledge and skills which complement his or hers.
Data
scientists use the ability to find and interpret rich data sources, manage
large amounts of data despite hardware, software, and bandwidth constraints,
merge data sources, ensure consistency of datasets, create visualizations to
aid in understanding data, build mathematical models using the data, present
and communicate the data insights/findings to specialists and scientists in their
team and if required to a non-expert audience.
Data
science techniques affect research in many domains, including
the biological sciences, medical informatics, health
care, social sciences and the humanities. It heavily
influences economics, business and finance. From the
business perspective, data science is an integral part of competitive
intelligence, a newly emerging field that encompasses a number of activities,
such as data mining and data analysis.
To
Learn More Follow Below Link:
No comments:
Post a Comment