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Understanding The Term Big Data, Data Science & Data Analytics On the Basis of Their Applications, Skills And Salaries
- Customer analytics
- Compliance analytics
- Fraud analytics
- Operational analytics
- Education: 88% have a Master's Degree and 46% have PhDs
- In-depth knowledge of SAS and/or R: For Data Science, R is generally preferred.
- Python coding: Python is the most common coding language that is used in data science along with Java, Perl, C/C++.
- Hadoop platform: Although not always a requirement, knowing the Hadoop platform is still preferred for the field. Having a bit of experience in Hive or Pig is also a huge selling point.
- SQL database/coding: Though NoSQL and Hadoop have become a major part of the Data Science background, it is still preferred if you can write and execute complex queries in SQL.
- Working with unstructured data: It is most important that a Data Scientist is able to work with unstructured data be it on social media, video feeds, or audio.
- Analytical skills: The ability to be able to make sense of the piles of data that you get. With analytical abilities, you will be able to determine which data is relevant to your solution, more like problem-solving.
- Creativity: You need to have the ability to create new methods to gather, interpret, and analyze a data strategy. This is an extremely suitable skill to possess.
- Mathematics and statistical skills: Good, old-fashioned number crunching. This is extremely necessary, be it in data science, data analytics, or big data.
- Computer science: Computers are the workhorses behind every data strategy. Programmers will have a constant need to come up with algorithms to process data into insights.
- Business skills: Big Data professionals will need to have an understanding of the business objectives that are in place, as well as the underlying processes that drive the growth of the business as well as its profit.
- Programming skills: Knowing programming languages are R and Python are extremely important for any data analyst.
- Statistical skills and mathematics: Descriptive and inferential statistics and experimental designs are a must for data scientists.
- Data wrangling skills: The ability to map raw data and convert it into another format that allows for a more convenient consumption of the data.
- Communication and Data Visualization skills
- Data Intuition: it is extremely important for professional to be able to think like a data analyst.
- The average a data scientist earns today, according to Indeed.com is $123,000 a year. According to Glassdoor, the average salary for a Data Scientist is $113,436 per year.
- The average salary of a Big Data specialist according to Glassdoor is $62,066 per year.
- The average salary for a Data Analyst according to Glassdoor is $60,476 per year.