What Is Data Science, and What Does a Data Scientist Do?

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SYNERGISTICIT
https//www.synergisticit.com/data-science
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What Is Data Science, and What Does a Data
Scientist Do?

• Is this data useful? Yes, very much. There are
  many insights that data can offer to the
  stakeholders and help them take concrete business
  decisions. This is where comes data science.

• Data is undoubtedly driving today's world. Every
  activity you perform online creates some data,
  whether you send an email, watch a movie, browse
  through your social media account or make some
  transaction. Can you guess how much data is
  produced every day? 1.145 trillion MB/day. And,
  it will surpass this number very quickly,
  considering the growing number of internet users
  every passing day. A source predicts that by
  2025, 463 exabytes of data will be created. Isn't
  it crazy? It does sound so.

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What Is Data Science?

• You must have heard this term pretty often these
  days. In fact, it is already optimizing your
  search results, influencing your recommendations
  and buzz feed, and so much more. In fact, data
  science is pervasive in industries grappling with
  loads of data and looking for ways to make sense
  of this enormous pile of disparate data. It is a
  study of data that combines many fields to gain
  extract the information present in the data.

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• Who Is A Data Scientist?

Data scientists are experts in data who know how
to find the meanings concealed in messy data
gathered from a number of sources. They perform
various functions on data to collect, organize,
clean, analyze it and finally visualize and
communicate the insights. With the help of
their reports, they help the business create
actionable plans for the future. They are
knowledgeable in various fields from software
engineering to programming, mathematics, and
statistics and work at the forefront for solving
business problems.
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What Does A Data Scientist Do?

• Data scientists can work in any industry, and
  depending upon the industry type, their
  responsibilities can be modified a bit, but in
  general, the duties are the same. So, here's what
  a data scientist has to do.

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• Writes data algorithms and modifies the existing
  ones to help maximize results and get solutions
  specific to the business problem.
• Go through relational and non-relational
  databases and integrate the structured and the
  unstructured data to the data lakes, warehouses,
  etc.
• Find out and transform the most optimal
  features/variables from the raw data for
  predictive modeling, improving the accuracy of
  the model on unseen data.
• Understand all the statistical and programming
  tools, libraries, and packages to choose from for
  specific data science applications.

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• Ensure the integrity of the data to get precise
  and reliable results and save time, money, and
  efforts wasted because of inaccurate information.
• Set up quality standards and fix data quality to
  tackle garbage in, garbage out (GIGO).
• Implement the best tools, framework, and
  algorithms for getting accurate results
• Figure out ways to leverage data for solving
  complex business problems and achieving business
  goals.
• Work collaboratively and communicate with other
  data team members such as data scientists, data
  engineers, business analysts, etc.

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• Mitigate the risks caused by the decisions made
  on erroneous data and statistics.
• Understand the industry, market, products, and
  services to help in the betterment of the business

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• Organizations across industries are looking
  forward to the data scientist who, with their
  expertise, can get them an accurate picture of
  what's happening to their businesses and how they
  can solve the underlying problems in their
  strategies and processes, taking a data-centric
  approach. Data science jobs will grow by 28
  through 2026 as estimated by the U.S. Bureau of
  Labor Statistics.
• The quickest way to get into this lucrative
  profession is through a data science coding
  bootcamp. It will help you acquire critical data
  science skills in a couple of months and qualify
  for numerous data science roles, including data
  scientist, data analyst, data engineer, machine
  learning scientist, business analyst, and more.

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Essential Skills For Data Scientists

• There are many core skills that a data scientist
  must possess to accomplish the tasks. Look at
  them below.

• Statistical concepts You should know about
  statistical tools and formulas to understand and
  identify the hidden patterns in data. Regression
  hypothesis testing, descriptive statistics,
  probability theory are some of the key concepts.
• Mathematics You should be familiar with
  mathematical concepts, such as arithmetic, linear
  algebra, calculus, geometry, probability,
  equations and graph, Bayes theorem as they help
  implement algorithms and perform analysis.
• Machine learning Knowledge of ML help simplify
  the data science tasks by automating them and
  improving productivity. ML algorithms help the
  machines learn on their own.

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• Computer science Computer science knowledge
  helps understand Big data, especially when
  working with concepts like map-reduce,
  master-slave, etc.
• Programming Knowledge of programming is a must
  for data science, and you should have familiarity
  with languages like R, Python, and SQL. It's
  useful in everything from analyzing large
  datasets to automating data organization,
  cleaning, and designing databases.
• Visualization and storytelling Data scientist
  has to communicate the results to the
  stakeholders so that they can take further
  actions based on the data. For this, you need to
  have exceptional visualization skills, putting
  the data in the form of graphs, tables, and other
  easy-to-understand representations and then
  narrating the insights drawn from it.

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• As you can clearly see, a data scientist is a
  multi-talented individual who has to have more
  than one skill. But this is not it. Besides the
  technical skills, you must have soft skills too
  to succeed in your field.

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• Business instinct As data scientists work
  closely with the stakeholders and help solve
  business issues. So, you need to have some
  business sense to help people get answers to the
  most pertinent questions.
• Analytical thinking You will be able to offer
  unique solutions to problems only when you
  identify them. Analytical thinking will help you
  identify the root cause of the problem and
  develop solutions that work the best.
• Critical thinking Many business decisions
  require complex analysis and data interpretation
  to offer a sensible and unbiased conclusion to
  problems. Critical thinks help data scientists
  cope with issues as they come.
• Curiosity Curiosity is necessary to go deeper
  and look beyond what's visible and known to
  discover hidden information within the data.
• Interpersonal skills You should be able to put
  across your findings to the team and make them
  accessible. Your communication skills should be
  brilliant.