The field of data science is often confused with that of big data. Data science is an aid to decision makers in a company with a logical approach.
Who is a Data Scientist?
A Data Scientist reviews a huge collection of data(that may extend to a couple of terabytes of disk space or thousands of excel sheets). This humongous chunk of data is not feasible for being handled, sorted and analyzed by a single person.
Here we require the help of data science, and most recently, the field of Artificial Intelligence has gained considerate limelight. With the use of efficient algorithms we can sort a huge chunk of data and also draw relationships with databases and metadata.
The Big Data and Data Science Confusion
Big Data: the today’s buzzword, literally means collecting a huge chunk of data based on events and interactions. Data Science manage the big data using calculus methodologies that is very different from traditional form of coding because these forms of codes are not used to deliver software and websites.
The Real World
In order to predict the outcomes of the future we have to analyze behavior trends along with extensive mathematical analysis like data mining, optimizations, predictive analysis. Big Data is one such source of information.
It is really exciting to think you can predict the future, considering the advancements in database management and machine learning. With the knowledge of linear algebra, probability and coding you get to dive into the real corporate world and quench your thirst for all your “what ifs”. And you can also turn profits for your company!
According to Glassdor, the job of a data scientist is one of the most flourishing profession in America. Data science provides a lot of information in your everyday life. To various degrees, data science influences your Amazon recommendations, popular interactive platforms, price comparison and gaming sites!
In Data Science you extract knowledge and insights from a large chunk of data. You collect and manage a large chunk of data with a lot of applications.
In different kinds of companies like finance, energy, travel and government, data science has found a lot of recognition. A lot of popular Universities provide courses and research studies in the field of data science nowadays. MIT and certain Universities in Columbia and master’s programs in UC Berkley, etc have given students the opportunity to study in the field of data science and have a career in the same.
The need of a data scientist is also growing exponentially. Wanted Analytics conducted a survey that reported that only 4% of 332,000 computer programmers in the United States currently have required skills in data science. The spike and want of people skilled for this particular profession has increased more because it has been found that analysis of data is essential for industrial growth. The Microsoft professional certification in Data Science gives you an overall knowledge in Data Sciences.
The necessary skills in data science are as follows:
- Educational qualifications: 88 percentage of people have a master's degree while 46 percentage of people have a PhD degree. The most common fields of study are mathematics, computer science studies and engineering.
- R language: R language is a preference language for development in the field of data science.
- Python coding: Python with a knowledge in Java, C/C++ is preferred for data science studies.
- Hadoop: Though it is not mandatory, it is heavily preferred to have knowledge in Pig or Hivee in a lot of cases.
- SQL: It is preferred to have skills to develop high level SQL codes.
- Intellectual curiosity: It is really necessary to have an intellectual curiosity and develop certain soft skills.
- Business acumen: As a data scientist you should be completely aware of the industry you're working in and discern what would prove as a leverage for your data. You should have a clear sense of decision making of what is an important and critical problem to be solve for your company.
- Communication skills: Companies are constantly finding people who can fluently translate the technical aspects to a non-technical language to be made understood to probably a sales and marketing department
What you can do to acquire the skills of a data scientist
To acquire skills of a data scientist is a challenging task but of course not impossible. There are of course requirements like a good mathematical base, clear concepts regarding analysis, coding, etc.
- Train yourself with computer, mathematics, engineering programs to gain expertise in this field.
- For MOOCs, Coursera, Udacity, etc are good places to start with
- Data scientists at Datascope Analytics helps with blogs to compare the different scopes in this field.
- Kaggle is a platform that hosts competitions for data science that helps you actually deal with real data and practical real-life problems. You can also work on relevant projects.
- You can join commute groups on LinkedIn to interact with people with same interests.
- Data Science Central and KDNuggets are good platforms to remain aware about facts in this particular platform.
Data Science is a really soaring field and opens a lot of opportunities. Machine Learning and Artificial Intelligence are requirements to deal with huge amount of data and industrial issues. In order to gain expertise one must start from being good with mathematics, algebra, coding and engineering and also work on courses and read blogs go further improve their skills.
Hence with data science a lot of real life problems can be solved.
