What is Data Science? Why is
it Important for Technology Professionals
Globally, we are connected, driven and ruled by data. The more data you analyze, the higher the competitive edge you have. Earthweb estimates that we generate 3.5 quintillion bytes of data daily. The demand for people who can analyze large datasets has risen due to the vast quantity of daily data generated.
Data Science is the collection, manipulation, storage, analysis and classification for further use. All the above actions help businesses take data-driven strategic decisions that minimize cost and optimize profit. Big data and its analysis is the next big innovation. Data Science professionals need to upskill, refocus and navigate their career goals to make the most of the situation. All technology-related jobs will be directly dependent, related to data science, or remotely connected. Professionals or candidates with the necessary knowledge of data management, visualization, SQL, Node, or Python will be top choices for promotion or for hire.
Important Skills Needed for a Career in Data Science
Data Science has a vast scope
in daily life, technology, and business operations. Given the technical nature
of the field, a few of the required skills are mentioned below.
● Programming Languages
● Statistics and Probability
● Database Management
● Machine Learning
● Deep Learning
● Data Visualization
●
Cloud Computing
● Data Analytics
How to Get into Data Science
To advance your career in Data Science, here are a few
classes courses to help you improve your skills. A skilled candidate is the
most desired one. Indulge in courses by Perfect E-Learning on Careervira to
enhance your hiring chances.
● Complete DataScience Course with Python by Perfect E-Learning: The course teaches necessary skills
like data analysis, data visualization, data preprocessing, Python, and Python
libraries. The module will enhance applied data science skills for projects.
The Careervira Take for this course emphasizes its credibility, pedagogy,
pricing and training. The 3-month program delivers the necessary technical
skills. The course is suitable for everyone with no prerequisites. The course
offers a 90% scholarship and gives EMI options to students. Certification is
only available after completing every test, project and quiz.
● SQL by Perfect E-Learning: The course teaches all SQL-related
skills like SQL commands, SQL language, data analysis tools, and relational
databases. Necessary technicalities like TCL, HCL, their clauses, operations of
SQL, benefits of joins, DML and DDL commands are covered in this module. It
also teaches types of joins, nested queries, triggers, domains and their
benefits.
● Database andNode (with Capstone Projects) by Perfect E-Learning: This intermediate-level course
teaches all about MongoDB and Mongoose. Mongoose and MongoDB is a popular NoSQL
database choice, with their smooth combination with Node. It teaches technical concepts
like browser JS, creating cookies in Express, REST API creation, creating the
first model, Node OS, and the difference between NoSQL and SQL DB.
● Python + DS +ML (Bundle) by Perfect E-Learning: OK Google developer has designed this course to teach Python. It
is the most favored programming language for creating data structures and
machine learning. The course will teach students to create machine learning
apps.
Best Jobs for a Career in the Data
Science Industry
If you are considering building a career in Data Science,
here is a list of top job opportunities.
● Data Scientist: This position is
relatively technical as compared to data analyst. Data Scientists must prepare
the data by cleaning, organizing and classifying it so that the companies can
take strategic judgments.
Top management uses organized data to make
data-driven decisions. They handle larger data sets to discover a pattern or
trend. They mine data to drive product and process improvement and help in
cost-cutting and quality maintenance.
Quoting Glassdoor, the average salary
of a Data Scientist is $126,468 per annum in the USA, £55,254 per annum in the UK, and
₹100,000 per annum in India.
Salary: DataScientist (April, 2023) | Glassdoor
Salary: DataScientist (April, 2023) | Glassdoor
Salary: DataScientist (April, 2023) | Glassdoor
●
Machine
Learning Engineer: Major work of a Machine Learning Engineer is to create data
funnels and deliver software-based solutions. They are responsible for running
tests and experiments to report the functionality and performance of the
system. They turn theoretical models into functioning models.
Quoting Glassdoor, the average salary
of a Machine Learning Engineer is $132,615 per annum in the US, £64,970 per annum in
the UK, and ₹100,000 per annum in India.
Salary: MachineLearning Engineer (April, 2023) | Glassdoor
Salary: MachineLearning Engineer (April, 2023) | Glassdoor
Salary: MachineLearning Engineer (April, 2023) | Glassdoor
● Data Analyst: They are responsible for solving all data-related problems.
They research and use data to find optimum solutions for minimizing turnover,
streamlining logistics, optimizing profit, and solving business processes.
They scrutinize complex data like
sales figures, assets, balance sheets, and consumer behavior. Their main job is
to provide faster, more productive, simple, and cost-effective solutions. Data
Analysts must maintain the accuracy and quality of data.
Quoting Glassdoor, the average salary of a Data Analyst is $70,272 per annum in the US, £37,972 per annum in the UK, and ₹610,000 per annum in India.
Salary: DataAnalyst (April, 2023) | Glassdoor
Salary: DataAnalyst (April, 2023) | Glassdoor
Salary: DataAnalyst (April, 2023) | Glassdoor
● Data Engineer: Their job is to explore, interpret and transform complex and large datasets into something easily understood and analyzed. Data Engineers maintain, develop, and test all the infrastructure committed to data generation. They must work with data scientists to get the necessary data.
Data Engineers are
architects of data-driven solutions. They help automate manual work, optimize
data delivery and redesign infrastructure for greater scalability.
Quoting Glassdoor, the average salary
of a Data Engineer is $115,339 per annum
in the US, £54,256 per annum in
the UK, and ₹880,000 per annum in India.
Salary: DataEngineer (April, 2023) | Glassdoor
Salary: DataEngineer (April, 2023) | Glassdoor
Salary: Data Engineer (April, 2023) | Glassdoor
● Data Architect: They help companies
to expand their market and grow. Their main job is managing, organizing, and
storing vast data in expensive electronic databases.
Data Architects are
responsible for creating comprehensive yet simple databases that the entire
organization can use easily. They study their employer’s needs and the scope of
data infrastructure to suggest needed upgrades and changes.
Quoting Glassdoor, the average salary
of a Data Architect is $73,692 per annum
in the US, £78,767 per annum in
the UK, and ₹1,024,029 per annum in India.
https://www.glassdoor.com/Salaries/market-analyst-salary-SRCH_KO0,14.htm
https://www.glassdoor.com/Salaries/united-kingdom-market-analyst-salary-SRCH_IL.0,14_IN2_KO15,29.htm?clickSource=careerNav
Salary: Data Architect (April, 2023) | Glassdoor
Conclusion
Almost every problem in the present world is solved by
data. Data-driven decisions are considered optimal and correct. Data science
helps make sense of large datasets but helps identify patterns and spot trends
for present and future uses. The real-time functional models pave the way for
automation. Big data is the century's innovation that has endless possibilities
in fields like business processes, daily commerce, consumer buying, marketing,
healthcare, automation, infrastructure, etc. The pragmatic choice is upgrading
the skill set to profit off the next big thing.
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Keep Learning, Keep Growing.
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