How much data engineer knowledge one must have to become a data scientist?
Today, it sounds like that every person want to become data scientist because in present it is amazing job to all and it has a great demand in market. Firstly, what is data science? — Data science is an interdisciplinary topic in which algorithm, processes, scientific methods and system to extract useful data from structured and unstructured data. Data science is a concept in which data analysis, machine learning, statistics and related algorithm are used. Both data scientist and data engineer lies under data science but both are somewhat different.
Who is data engineer?
A data engineer is an employee whose tasks are to prepare data for operational or analytical uses. It can be different from organization to organization. It can be integration, consolidation, structuring, etc of data. Data engineer mainly deals with both structured and unstructured data. With that data they have different approaches to work with that data. They also works as analytics team to give ready data to data scientists. They also work with business department to provide data aggregation to business executives, business analysts and more business user who deals with that data.
SQL, scala, Ruby, Python, C, C++, Java are skills that are well known by a data engineer. They also should have knowledge of extract, transform and load tools and REST-oriented APIs for construct and managing data integration data.
Who is data scientist?
A data scientist is an employee who collects, analyze, and interpret large quantity of data to find future prediction of a business. They deal with big data i.e. very large amount of data that is difficult to store or analyze. A data scientist must have a great knowledge of mathematics, statistics, programming, and have a creative knowledge to deal with the data. Their main work is to collect useful or meaningful data from big data and analyze that data and virtualize the data.
Soft skills and communication skills are also important for a data scientist. They should present their project like storytelling so it is easy for the audience to understand. They should have a great knowledge about big data platforms and tools, including Sparks, Hive, Hadoop, and MapReduce. Programming language such as SQL, Python, Scala, R, etc. are the requirement for a data scientist.
How to become data scientist from data engineer
Firstly, we will see about common thing in data scientist and data engineer
If you are a data engineer and want to become data scientist that you should have a great or deep knowledge of data science. You should understand how a data is virtualized better than the average data scientist and how to present data effectively or which data is best fits to a problem. Data engineer need to focus much on mathematics, statistics and creativity. They need to gain more knowledge about business and working of that business and how they can increase the efficient working of business organization.
Some main important improvements for data engineer to become data scientist
· More knowledge about data science and big data.
· Want to improve more knowledge about mathematics and statistics.
· Want to improve communication and soft skills.
· Want to think very creative.
· Want to learn new tools of data science like Research analysis, SAS, modeling, ML and AI i.e. machine learning and artificial intelligence, etc.
· Want to more focuses on business prospective.
· Want to get more familiar to data that which can be used in which problem and to explore to find hidden pattern.
· Want to present their data like a story telling .
Conclusion
However, today data scientists are the talented job because this job has much scope in the industries. If there is a good data scientist in an organization than there possibility to increase streamline processes, user engagement and predict the future analysis and they have great demand in ITs. They have been highly paid. To have a good value in market you should have to acquire above skill set.
