There is a sudden surge in the demand for data scientists today. Around half a million such jobs are likely to be created across the world in the future. Even India’s Big Data Analytics sector presents a rosy picture now as it is set to grow into a $16 billion sector soon.
Certified data science training course have the adequate scope and optimistic future. According to Glassdoor, the median salary of a data scientist could range over anything around $100,000. So, there is a humongous amount of job prospects in Data Science.
The data science certification is necessary for the aspiring engineers to understand the practical nuances of Big Data and executes such data for meaningful information. Data science is all about how efficiently a person can manage the ETL (Extract, Transform, and Load) part while unscrambling its wrangling proportions.
Data science is not just about analytics but understating the latest programming languages like MapR and Hadoop for successful execution of the company’s technical goals and policies. From the basics of big data to data analytics life cycle, a professional course is necessary to grasp the nitty-gritty of data science.
What Does a Data Scientist Do?
Until now, data science was construed as a simple job of feeding data into the system and gets the desired output. However, in the last few years, the subject matter of data science has become more complex than ever. A person handling the company’s data needs to ensure that the values he feeds into the system should make sense before turning them into algorithms.
Exploratory Data Analysis or EDA is the cornerstone of data science projects. It assists engineers to identify patterns and develop a hypothesis while drawing inferences from another data analysis.
Traits of a Successful Data Scientist
- Leadership capabilities: A data scientist leads the company’s data-driven He is the one who sets goals and Key indices to keep a tab on a company’s growth prospects.
- Ability to Articulate: A data scientist should able to express whatever he grasps from data mining. He should convey the same to the management for better implementation of company goals.
- Team player: A data scientist spearheading a particular data campaign should be a team player. The team first discovers potential business questions and then tries to solve, define strategy and pursue the company’s objectives.
- Versatile Abilities: A data scientist should be flexible enough to adopt a different level of expertise and skills along with utilizing his natural language processing skills before drawing any conclusion. In all advanced data analytics, a lot of interdisciplinary knowledge is required.
- Professional Knowledge: Data science is a vast subject and requires a thorough knowledge of programming languages like Python, SQL, Java, and C++. Experts recommend data science certification for all aspiring data scientists before entering into this profession.
Professionals can independently manage big data tools like Hadoop, MapR, and Madlib functions after completing data science training programs. For more details on this program, get in touch with join@cognixia.com.
