Please enable JavaScript.
Coggle requires JavaScript to display documents.
Data Science - Coggle Diagram
Data Science
This discipline allows data to be useful.
Since the world became interested in analyzing information, this caused an information overload to begin to be generated and at the same time, several concepts like
data analytics
and
data science
emerged to be able to classify this new area.
Data science
In general, they
both work with data
, but the
difference
is
what they do
with this data.
It´s focused on finding actionable insights from
large sets of raw and structured data.
There are used several techniques like computer science, statistics and predictive analytics in an effort to
establish solutions to problems that haven’t been thought of yet.
It tries to predict potential trends, explore disparate and disconnected data sources, and findg better ways to analyze information.
Difference
Scope:
Data science is an umbrella term for a group of fields that are used to mine large datasets. Data analytics is a more focused version of this and can even be considered part of the larger process.
Goal:
Data science isn’t concerned with answering specific queries, instead parsing through massive datasets in sometimes unstructured ways to expose insights. Data analysis works better when it is focused, having questions in mind that need answers based on existing data.
Data science
produces broader insights that concentrate on which questions should be asked, while
big data analytics
emphasizes discovering answers to questions being asked.
Data analytics
Focuses on processing and performing statistical analysis of
existing datasets
.
Its focused´on creating methods to capture, process, and organize data
t’s based on producing results that can lead to immediate improvements.
Big Data
Refers to
massive and often unstructured data
, that exceed the capacity of common software to be captured, managed and processed in a reasonable time.
With the birth of the Internet and the growth of the technology sector, there has been a disproportionate
increase in the volume of data
, causing:
A problem that has arisen is being able to determine the
veracity
of the increasing data
The need of mechanisms that can process the data at a speed in
real time.
Not only having
structured data
(dates, keys, amounts, time, etc.), but also having
unstructured data
(blogs, comments on social networks, tagging in photos, videos, etc.)
Importance
Data Science
Reduce Costs
Reduce time
Take decisions more informed and fundamented
Optimize the offer based on customer´s habits.
Develop new products.
Big data