You will find a number of complex definitions for Data Science. Well, here is the meaning of Data Science in simple terms. It is a study which mainly focuses on the data. The data can be either structured or unstructured, data science is used to gain insights, analytical patterns, reasoning, etc. from the data. It is required to break down complex problems and solve them. It is a multidisciplinary blend of many things. These things include algorithms, data, technology, linear algebra, complex mathematics, calculus, etc.
Data Science is more closely related to mathematics and its different fields. It is somewhat similar to computer science but still has some differences. Computer science is used for coding and programming to process data and perform different functions as per requirement. On the other hand, data science is used for deriving analytical patterns, extract different types of data and the organization of data. Data science works with other fields like machine learning, big data, deep learning, etc.
Data Scientist and Skills for becoming a Data Scientist
The person who practices data science is known as a data scientist. Data Scientists are the extraordinary professional that manages both the business and IT work for a company. They are a combination of many skills. Their skills include being a mathematician, computer scientist, programmer, leader, etc. This is one of the reasons why they are amongst the highly paid IT professionals. Many IT services company and other cities pay a lucrative package to such professionals. Most of the students and professionals aspire to become a Data Scientist. But the journey to becoming a data scientist is not an easy task.
There are many factors that you need to take care of and the skills you need to build. Also, some people have the misconception that only an experienced person can become a data scientist. Even if you are not experienced, you can still become a data scientist. Multinational companies are searching for fresher candidates at a data science position and you must remember that knowledge is preferred over experience. If you want to become a data scientist, then you must follow these important and effective tips and skills.
1. Education – Education is the first and foremost requirement to get into the data science field. You need to be a post-graduate candidate for becoming a data scientist. First, you need to attain a bachelor’s degree in the field of IT/ Computer Science/ Physics/ Mathematics or any equivalent field. Then, you have to attain a master’s degree in Computer Science/ IT/ Data or any other field which is equivalent.
Once, you are done with the post-graduation, you can start searching for the job. It will be better to have some internship or certification or some work experience. With the help of these certificates, you can easily get employed. Along with these, you require other skills too, these are analytical thinking, linear algebra, statistics, etc.
2. Mathematics and Statistics – As it is discussed above, data science uses mathematical concepts in abundance. Hence, you need to have great mathematical skills. Some of the mathematical topics required are reasoning, probability, linear algebra, discrete math, calculus, etc. Since data scientists need to make business decisions and formulate plans, they require facts and presenting and analyzing the data.
Also, data science deals with the presentation and analysis of data for which statistics and probability skills are required. Hence, it is really essential that a data scientist is excellent in mathematics and statistics.
3. Machine Learning & Deep Learning – As data science works on both structured and unstructured data, it uses the machine and deep learning concepts. Machine learning is the study of making a machine intelligent. Deep learning is a field of machine learning that has advanced concepts in which a neural network is created to mimic the function a human performs. Data science requires these fields because, with the help of them, efficient algorithms can be made which will help businesses in identifying the potential risks and opportunities. Therefore, your machine learning and deep learning concepts should be cleared.
4. Python, SQL, R – These are the languages that a data scientist must have handy. In-depth knowledge of these programming languages is essential. Python is the most popular language among machine learning experts. Python provides libraries that make it easier for developers to create algorithms and models.
Data science also includes data mining and warehousing concepts. As it is the study of data and deals with RDBMS (Relational Database Management System), it is required that the candidate is aware of SQL. It helps in various types of data mining and normalizations used for data management.
R is a very powerful programming language. It is faster than some other programming languages developed by R foundation. Data visualization, computation, and manipulation can be done at a faster pace with the help of this language. It is a popular choice of data miners for data analysis. Therefore, the knowledge of these languages is required. It can help you get employed in a renowned IT services company.
5. Practice and a lot of Practice – There is no denying that if you want to become an experienced and specialized professional, then you need to be well-versed with the methods used to perform a task. A similar thing implies to the data science field. The experience will help you in generating critical skills like risk identification and making realistic plans, etc. No one is perfect but daily practice can make you better and improve your performance.
6. Data visualization – Data Science is a superset of data visualization. Many people confuse data science with data visualization but these are two separate terms and entities. In data visualization, the data is presented in a graphical format. Because data science also focuses on data presentation, the data is converted into different graphical objects. Graphical objects include lines, bar graphs, pie charts, etc.
Data visualization helps in organizing the data. If the data is organized in a structured format, then various decisions can be easily taken. Hidden patterns in the data can be identified and can be used for studying insights of risks that can occur or some also identify the potential opportunities that the business can use for its success.
7. Communication and Management Skills – Data scientists are also responsible for taking analytical and managerial decisions. They have the qualities of a leader and a manager. It is important for leaders or managers to have communication skills. They have to communicate their ideas, thoughts, plans to explain others.
Also, they have to direct, control and inform others about how things will be done. Communication skills are also required for taking managerial decisions and giving presentations. Hence, make sure you work on your communication skills as it is the key skill which is required in almost all the sectors.