Data Scientists are similar to analytical data experts, and they need to be well versed with technical skills so as to identify and understand which problems need to be solved and then solve the complex problems. They are called to be part mathematician, computer scientist and trend spotter. The career of a data scientist begins as statisticians or data analysts. Data scientist job has been declared as the most productive job of 21st century, after this many graduates and masters have got attracted to pursue Data scientists as their career field.
Data Scientist is someone who needs to have mixed proportion of being good at statistics and also at software engineering. The process to follow in order to become a Data Scientist is as stated below:
1. Ensure to be stats. Math and machine learning expert
Maths, Statistics and Machines are the base of data scientist. You need to gain an expertise in all the 3 fields so as to become a successful data scientist. Just mugging up the concepts will not work effectively; you need to get practically trained on these concepts through a data science course, as only this will make the base of your data scientist career stronger.
2. Develop better understanding of databases
During the course of your college learning, you will be working with data in text files. But once you enter the job field and start working as a Data scientist the scenario will not be the same. Database is used to store the data. It will be stored in MYSQL, Postgres, MongoDB, Cassandra etc. To effectively perform your job operations you need to well versed with all these data storage softwares.
3. Learn to Match Up with the Big Data
The process of working with small data is different and on the other hand for the big data is different. When you start working with the data at the scale of web, the analysis process and approach towards the data needs to be changed and improvised. The major problems majority of the data scientists are facing is not being able to run on single machines as they have large data which demands distributed processing.
Also Read: Importance of Big Data for Business
4. Expertise in Coding
Coding is the basic requirement of becoming a data scientist. To become a successful Data Scientist you need to learn and understanding coding well. All your computer fundamentals need to be clear. Develop an understanding on grasping end-to-end development as your inventions will be integrated with other systems. Choose the first language for coding and focus on learning interactively.
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5. Become a master of data Munging, Visualization and Reporting
Data Munging is a process where the raw form is converted into another format so as to ensure its effective and easy consumption. Data Visualization is a process of creating and studying the visual representation of the data. Reporting is the end process where the analysis and results are presented in a comprehensible report. A data scientist needs to be a master in all these processes to assure considerable growth and development.
6. Engross in Practically training yourself
To utilize all your learning and to identify if you are a true data scientist you need to enter the job field where you will be practically examined. You can start your practical journey through an internship, bootcamp or getting a full time job for yourself.
7. Engage yourself with the community and communicate with fellow data scientists
Practice to learned skills; meet fellow data scientists to know more about this field. Follow different sites and the experts of this field. All this will help you to polish your skills in a better way and will also make you aware with minute details of Data Scientists.