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On Penetrating the Complex World of Data Science

December 27, 2018 12:21 PM

Data Science has emerged to be one of the hottest and trending careers in the present day and age, with more demand and shortage of eligible candidates. Data Science holds a lot of scope and will be one of the fastest growing industries in the coming times.

Let us attempt to understand what Data Science is all about, its scope and how this field will impact the world at large.

What is Data Science?

Data Science is an amalgamation of programming, mathematics, statistics and design which are roll-balled together and applied in order to successfully manage a digital data collection. The three core components of Data Science are organising, packaging and delivering data. In totality, it can be referred to as a multidisciplinary blend of data inference, algorithm development and technology in order to solve analytically complex problems.

Data Science is not too different from Data  Mining in the sense that it attempts to extract  knowledge and insights from data in various  forms, either structured or unstructured. It is a ‘concept to unify statistics, data analysis, machine learning and their related methods’ in order to ‘understand and analyze actual phenomena’ with data.

 There also exists a very fine line between a Data Scientist, Business Analyst and Statistician.

An Analyst is involved in operations pertaining to Business Administration and Exploratory Data Analysis. A Data Scientist is involved with Data Product Engineering, Machine Learning and Advanced Algorithms.

A Data Analyst tries to explain the proceedings by processing history of the data, while a Data Scientist does both the exploratory analysis in order to discover insights and uses several various advanced machine learning algorithms to identify the occurrence of a particular event in the future. The latter will identify unique angles and will make decisions and predictions through predictive causal analytics, prescriptive analytics (predictive plus decision science) and machine learning.

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 The Roles and Responsibilities of a Data Scientist

Data Scientists are people who perform Data Science! They perform research, analyse data and help companies in flourishing by predicting relevant growth trends and business insights based on their data mining skills. Data Scientists take huge chunks of data and use their skills statistics and programming to clean and organise the data. All this wrangling combined with relevant industrial knowledge helps in uncovering hidden solutions to business challenges.

A Data Scientist must accomplish the following tasks in his/her everyday life:

  • They must know the output of the huge chunk of data they are analysing.
  • They need to devise a due plan to comprehend as to how the desired output can be reached with the given resources and time.
  • To achieve this objective, a Data Scientist must perform due research on the messy data and frame questions which would be answered by his analysis on the same.

What does it take to be a Data Scientist?

Data Scientists are highly educated. Reportedly, around 88% of them have a Masters’ Degree PhDs, with most of them having a strong educational background in general. To become a Data Scientist, one must possess a Bachelor’s degree in Computer science, Social sciences, Physical sciences, and Statistics. Most students subsequently for a Masters’ Programme or online certification programmes to learn Hadoop and Big Data querying. Alongside, you need to be proficient in SQL Database/Coding and Data Visualisations, besides knowing the basics of R Programming.

The Scope of Data Science

As per a 2017 Forbes Report, the prospects in Data Science are tremendous. More than 190, 000 data scientists were needed in the year 2018. This number doesn’t include the 1.5 million analysts and leaders required to work on the big data supplies. It goes without saying that in this era of technology where more and more jobs are being created in Automation, Machine Learning, Robotics and Artificial Intelligence, Data Science holds its ground and holds potential to move up on the value chain and carve out a space for itself where machines find no role to play.

Data Science stands amid one of the fastest growing industries at present and requires one to stay abreast with the latest trends in technology, job opportunities and related tools. Besides the aforementioned educational qualifications requited to be a Data Scientist, one can get certain certifications to obtain a junior role and break into the said space.

The Pay Scale of a Data Scientist

The field of Data Science is for people having a penchant for analysing and explaining information in an intriguing way. The career of Data Science is suited for people who have an analytical and mathematical bent of mind and can immerse themselves in a sea of data. Having additional technical skills like coding, computer science and end-to-end development also helps.

As per a University of Wisconsin Report, a Data Scientist draws an average salary of $113, 436. The salary of a Data Scientist depends on various parameters like experience, job title, industry, company size, region and education.

A recently published 5th-annual Burtch Works Study: Salaries of Data Scientists cites being a Data Scientist as of one the sexiest jobs in 21st century. Data Scientists with a PhD earn the highest median base salary of $102, 000 while those with a Master’s degree earn a median base salary of $92, 500. They apparently earn base salaries up to 36% higher than other predictive analytics professionals.

It is predicted that by the end of the year 2018, there will be a need for around 1 million Data Scientists. The world is deluged with data and requires driven, highly skilled and motivated Data Scientists to have a crackdown of the most complex problems.

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