Understanding Data Science Under 1000 Words

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Understanding Data Science Under 1000 Words
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Data is the new oil. In 2006, Clive Humby,
UK-based mathematician and the man behind Tesco
Clubcard, coined this phrase and changed the face
of the world. According to him, data is vital for
survival, but unrefined data is of no use like
oil. Tech companies are trying to filter and
utilize consumer data to create better services
for their consumers. And who is filtering out the
data? Its the data scientists.
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The new age of engineers and professionals is
joining a Data Science Bootcamp to upgrade their
skills and future-proof careers. HBRs
revolutionary article Data Scientist The
Sexiest Job of the 21st Century, published in
2012, brought data scientists into the limelight.
The report labeled them a new breed of
professionals who could analyze, track, and
predict consumer behavior by filtering and
investigating the data. Here, we will try to
explain data science and the fundamentals of the
subject in less than 1000 words.
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• What Is Data Science?
• Data Science is a multi-disciplinary field
  combining machine learning, computational
  science, and business knowledge. In this field,
  data scientists sieve through a vast volume of
  data using analytical tools and algorithms to
  derive meaningful patterns that interpret
  consumer behavior.

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Data science has revolutionized our world, making
it better and more efficient. It helps predict
and identify the root cause of a disease or
epidemic, improve healthcare for patients, or
optimize traffic routes to prevent traffic
congestion.
Why Become A Data Scientist? Data science is a
lucrative field. With companies becoming more
data-driven, there is a rising demand for skilled
professionals who can interpret unfiltered
information and unearth underlying patterns. And
these agencies are willing to pay a handsome
amount to recruit them.
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• According to Glassdoor, a data scientist is the
  third most promising position among Americas top
  50 jobs in 2022. The median base salary is
  approximately 120,000. It is an exciting career
  with stability and high job satisfaction.
• Apart from that, a data scientist learns various
  skills, including programming, statistics, and
  business analytics, that makes their career
  future- and industry-proof. These professionals
  can work in multiple industries with the given
  set of skills. Also, a data scientist does not
  require a physical office to work. They can
  handle the task remotely, working on the
  deliverables from the comfort of their home.

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• Prerequisites for Data Science
• Data science is an in-demand skill among
  recruiters. Every organization is trying to be
  more data-driven and actively hiring skilled
  professionals to help them achieve this goal. It
  is a lucrative field and offers excellent pay.

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• Candidates planning to enroll in a data science
  program or a coding bootcamp do not require a
  prerequisite degree in computer science. A degree
  in the STEM disciples can surely help in sailing
  through the course, but its not a deal-breaker.
  Ideally, a preliminary understanding of machine
  learning, programming, and statistics can make
  the program easier to grasp.
• Must-Have Skills For Becoming A Data Scientist
• Mathematics In data science, numbers hold a
  particular position. Anyone planning to become a
  data scientist must have a strong understanding
  of linear algebra and quantitative arithmetic.
• Programming Data scientists sieve through years
  of data with the help of complex algorithms and
  programming tools. Proficiency in programming
  languages like Python, SQL, and Java is expected
  from a data scientist to analyze, catalog, and
  translate the information into a decipherable
  pattern.
• Project management Managing and handling the
  project is crucial for deriving the results by
  the assigned deadline.
• Data Science Life Cycle
• The data science life cycle is roughly divided
  into five phases, accumulating the data to
  communicate the finding. It is a lengthy process
  and can take a few months or more to reach the
  end-stage.

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• Five stages are
• Capture The data scientist gathers raw,
  unfiltered information in this phase.
• Investigation and sorting In this phase, data is
  cleaned, sorted, and cataloged for analysis
• Processing Here, the data is processed,
  analyzed, and clustered to uncover the hidden
  patterns in the pool of data
• Analyze It is the most critical step of data
  mining. Here the data scientists study the clean,
  sorted data and patterns to provide predictions
  or models for companies to run
• Evolution and Deployment The model is tested and
  verified for its accuracy and error margins in
  the last stage.

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• Tools Used By Data Scientists
• These professionals use multiple tools and
  algorithms to go through a massive chunk of data.
  MS Excel is preferred by freshers starting with
  data science before progressing to high-end
  analytic tools.
• Some of the standard tools used by data
  scientists include
• Tableau
• Azure ML studio
• SAS
• Informatica/ Talend

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Conclusion Data science is an in-demand sector
among companies and recruiters. You, too, can
join the Best Data Science Bootcamp by
SynergisticIT and join this budding field for a
prosperous, satisfying career. During the
program, you will learn the critical principles
of the subject like AI, Machine Learning, and
data visualization. And at the end of the course,
you will receive an industry-recognized
certificate that can boost your career.
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