Data
is everywhere Indeed, the amount of existing digital data is growing
rapidly and is expected to increase to 180 zettabytes by 2025.
However, much of this data has only recently been used in analytics to find
insights. That's why more and more companies are looking for institutions
and experts to make data meaningful.
Being a data scientist is not difficult. After mastering the skills of
data analysis, you will need to practice your new skills well enough to become
a proficient expert.
In this article, we'll look at what data science, big data and data analytics
are and where they are used, and what skills are needed to be an expert in this
area.
Similar to data mining, data science is a
convergence field that uses scientific methodologies, processes, algorithms,
and systems to extract knowledge and insights from a variety of data, including
structured and unstructured forms. Data science is also defined as the concept
of integrating methodologies associated with statistics, data analysis, and
machine learning to understand and analyze real phenomena through data.
It is characterized by focusing on the
development of a technology to handle them or properties that are common to
data of different properties or formats rather than specific contents of the
data.
However, much of this data has only recently been used in analytics to find insights. That's why more and more companies are looking for institutions and experts to make data meaningful.
Being a data scientist is not difficult. After mastering the skills of data analysis, you will need to practice your new skills well enough to become a proficient expert.
In this article, we'll look at what data science, big data and data analytics are and where they are used, and what skills are needed to be an expert in this area.
No comments:
Post a Comment