Beginners Guide to Data Science

Beginners Guide to Data Science

Data science is the study of data like bits, numbers, images, texts, etc. gathered from multiple sources like web servers, logs, databases, APIs, online repositories and so on by using scientific methods, processes, algorithms, and systems to obtain information from any structured and unstructured data.

Finding the right data to either drive a business decision or come up with a new product feature or an interesting story takes both time and effort. Understanding what you can actually do with your data is very crucial, in order to optimize the process and handle many complex scenarios dealing with inconsistent data types, data science helps in the data preparation by cleaning the data and transformation of data using certain tools which helps in understanding the data structure better to define and refine the selection of feature variables that will be used in the formation or development of business models.

Why learn Data Science?

Data Science is a big leap in technology. The idea of data-driven business is of high demand and growth. Data Science related jobs have been claimed to be the most sought after jobs today. It is not just the interesting content and demands of the jobs that make it an exciting profession but also the prolific salary package attached to it. Businesses are looking for more and more data scientists to help them adopt a data-driven approach.

Big data is growing and everywhere. If you look around a lot of data is being collected and warehoused like web data, e-commerce, purchase department, grocery stores, sensor data, IoT data, social media, customer interactions, bank transactions, telecommunications, sensors, intelligent devices and many more. This data in its oversimplified form is called big data. To understand big data is to understand data in its most complex form. It is this understanding that can potentially lead to answers to ambiguous questions.

Grow a new stream of profits.  Many tech organizations already have a data-driven operation model in their operations. Be it the core of decision making with businesses adopting a more detailed data-driven approach, the data science departments are becoming crucial to their sustenance. Hence, working in a data-driven business as a data scientist one will always be at the core of decision making.

Data-Driven Analytical Thinking. To look at data and inform actionable results is the need of the hour. More than just a need, it is a skill that will come handy in all walks of life. Though it begins with analyzing data it eventually leads to data-driven thinking.  


Data Science Components

Tools for Data Science

Data Science is Changing the World

The availability of the data and understanding of the data models that the industrial world is using is complex. Data science is really all about building models on any kind of data that represents the physical phenomenon.

Data science offers a full set of machines that will allow industrial developers to create their own software to solve the problems of improving the performance, operation, and cost of assets throughout the whole spectrum of an industrial complex. One of the examples would be a predictive maintenance model.

The predictive maintenance platform is a cloud-based operating system that combines a set of services in such a way that the industrial internet will be able to apply all these techniques to solve the problems.

The platform has the data which helps in figuring out how to predict when something is going to break rather than fixing it after it breaks.  Predictive models are based on some combination of history, physics, and all the information that is available.

Few scenarios like the airline companies can now easily predict flight delays and notify the passengers beforehand to enhance their travel experience.

With data science, it is possible not only to predict employee attrition but you also understand the key variables that influence employee turnover. Logistic companies have discovered the best routes to ship, the best suited time to deliver and the best mode of transport to choose that leads to cost-efficiency. Genomic data provides a deeper understanding of genetic issues and reactions to particular drugs and diseases. 


Data Science Workflow


Data Science Job Roles

  • Data Analyst
  • Machine Learning Engineer
  • Deep Learning Engineer
  • Data Engineer
  • Data Scientist


Data Science has taken the world by storm, as a data scientist one can be a specialist in statistics, data science, Big Data, R programming, Python, and SAS. A profession as a data scientist assures a plethora of opportunities and well-paying salaries.

Data Science job opportunities are unlimited, and specialists with data proficiency will persist to drive the technology revolution. Industries are utilizing Data Science to improve their invention, business evaluation, and marketing efficiency. There has been a 29% increase in demand for data scientists year over year and a dramatic upswing of 344% increase since 2013.


Check out all the latest data science courses here.

Got any questions?? Comment below.

Written By


Rini is an auto, technology enthusiast who has majored in Automotive embedded systems. Currently, she is working as a technology career counsellor at Skill At Will to help individuals identify their career paths in tech and help them build a better career. She enjoys enlightening others through her technology blogs and articles.


Comments (6)

Udaya Troy

May 21, 2020 08:24:10 PM




May 21, 2020 10:01:11 PM

Nice read! Companies like SAP helps users to develop and execute workflows based on data stores



May 21, 2020 11:39:04 PM

Precise information.



May 21, 2020 11:49:47 PM

Very informative and well explained



May 21, 2020 11:51:20 PM

Very informative article. Thanks



May 22, 2020 07:57:59 PM

Simple with indeed informative .


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