THE THREE MUSKETEERS OF DATA

Since the launching of the Internet, the amount of Data produced is increasing exponentially. It is estimated that by the year 2020, for every second of time that passes, and for every human being on Planet Earth, approximately 1.7 Megabytes of information is being created. Three major Scientific Disciplines based on the accumulation and use of Data are now competing with each other for attention, and the best young minds are vying for a place in the sun. This article studies the phenomenon of these Three Disciplines – Data Science Vs Big Data Vs Data Analytics.

Some Explanations

Following are short meanings of the Three Disciplines

• Data Science: This is a field that converts both Structured and Unstructured Data to a meaningful extraction, comprising Data Cleansing, Preparation and Analysis. Subjects like Mathematics, Statistics, Problem-Solving, Programming and Thinking Out-of-the-box form a combination of tools by which this Science tries to understand and manipulate Data. 

• Big Data: This describes the condition of Data Flooding, on a day-to-day basis of small to large businesses or organizations, and how to control this vast inundation of Data. 

• Data Analytics: In this field, Raw Data is analytically examined by application of mechanical process or Algorithms, in order to extract meaningful insights, by the use of existing or new models.

DataMites provides data science training in Bangalore, Chennai, Hyderabad and Pune. Join best classroom program and get certified as ‘data scientist’.

Some Applications 

Some of the Applications of these Sciences are:

• Data Science: Recommender Systems are an application where the User’s previous search results are used to locate relevant products from the billions of Products available. Other applications are Digital Advertisements and Internet Search.

• Big Data: Often used for Financial Services, such as Retail Banks and Credit Card Companies, some other applications are Customer Analytics, Operational Analytics, Compliance Analytics and Fraud Analytics. Also applied in Communications and Retail.

• Data Analytics: The main areas are in Gaming, Energy Management, Health Care and Travel.

Some Skill Sets

These are:

• Data Science: Here High Education is most important and Masters Degrees and PhDs are almost a must. ‘R’ is the preferred language, but ‘SAS’ is also used. Coding Languages like ‘Python’ is mostly used along with JAVA, EERL, C / C++. SQL and Hadoop Platforms are common, but most important is experience in dealing with Unstructured Data.  

• Big Data: Mainly Mathematical and Statistical skills, combined with Computer Science, Business and Analytical skills, are all important, but Creativity is absolutely essential.  

• Data Analytics: Here, all the other skills enumerated above may be required, but in addition Machine Learning skills and large Data Formatting abilities are most important.  

Some Typical Salaries

Both Data Scientist and Big Data Specialists make around the same average salary (around US$100,000 p.a.). Data Analysts make nearly 60% of that per year. 

Conclusion

The salaries in these fields are some of the highest paid to Professionals in Industry. But the work is very hard, and hours are often long. Data Science Vs Big Data Vs Data Analytics is a battle that is best fought by the Candidate competitors themselves.