Data science is a branch that involves use of scientific methods and multiple algorithms to extract the information from any structured and unstructured data. A data scientist has to be well versed in computer science, statistics, and mathematics. They have to deal with large sets of structured and unstructured data.
Depending upon the present and past patterns, a data scientist is expected to predict the future. To be a data scientist, you must possess the ability to solve complex problems. Overall, a data scientist has to extract the information and interpret the data.
A data scientist has to use a lot of programming languages for the collection of data and its analysis. They must understand the sector or area in which they are working and solving the problems. They should have technical skills like a programmer and non-technical knowledge along with good communication skills. These skills help data scientist for analyzing the data correctly and efficiently.
There are various technical skills that a data scientist should have and that are Statistics, Machine learning tools and techniques, Data mining, Data visualization, Programming languages, etc.
A data scientist finds the questions and helps to solve them that will benefit the business whereas, a data analyst has been given the questions to solve. A data analyst job is to analyse the data and to know the reason if there are any changes in the data. Data scientist job is to identify what will happen or to predict the future from a given data.
A data scientist needs to have a lot of technical skills and non-technical skills. Some of the important skills required for a data scientist are mentioned below:
Programming languages are very important for data scientist.Apart from many other skills, this skill holds great importance to become a data scientist.
Python is a common coding language because of its versatility and huge library. It can be used in all the processes of data science. SQL is also one of the important language for data science. SQL is very helpful in carrying out operations like adding, deleting, or extracting data from a database. Expertise in SQL will help you save a lot of time because it is specifically designed to work on complex data. Python and SQL are the most important languages that a person must know if he wants to enter in the field of data scientist.
Machine learning gives precise results and analysis as there is no chance of human error. It can develop efficient algorithm for the processing of data. The reason why machine learning is important for this job is that it provides better output and results and gives high value predictions. You can easily analyse a lot of complex data with the help of machine learning.
Data scientist have to deal with a lot of data so it becomes important for them to know about data management. Apache spark is a big data technology that helps in running the complicated data faster. Apache Spark helps data scientist to stop the loss of data. Hadoop distributed file system also helps in storing your data across various hard drives. Both Hadoop and Apache spark are data computing framework but Apache spark is faster than Hadoop.
Communication skills are must because a data scientist have to translate their technical research to the non-technical department. Similarly, they should be able to understand the details provide by non-technical department for better analyzing of data. They have to present the data in such a way so that it is easily understandable by everyone and this is why having communication skills is important.
It is one of the toughest skill that a data scientist should have. Data intuition mainly comes from experience. You must have a good understanding of all the concepts. Data intuition is about finding the patterns when they are not easily visible. It is very difficult job and that is why your concepts should be clear.
Data scientist have to deal with a lot of unstructured data. So, a good understanding of statistics is required for doing quantitative analysis of data. There are various statistical data analysis methods for analysis of data such as Hypothesis testing, Regression methods, Time series analysis, etc. Statistics provides the methods and tools to analyse the data in detail.
Basically, if you want to start your career as a data scientist then you must have knowledge about Maths, Statistics, and Programming language. These are the basics of data science.
Job of a data scientist requires a lot of skill and hard work and that is why you get handsomely paid. It is not an easy job as there are a lot of things that you should have a good knowledge about. There is a growing demand of this job and also the field of data science is still evolving. Hence, it is a perfect job and if you have the required skill then you must go for it.
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