DATA SCIENTIST Vs DATA ENGINEER

Data Scientist and Data Engineer   may be new job titles, but the basic job roles have been around for a while. Traditionally, someone   who   analyse   data would be called Data  Analyst  and anyone who created backend platforms with data analysis  would be “Business Intelligence Developer (BI).”

With the arrival of large data, new roles began to appear in companies and research centers – namely, data scientists and data engineers.

data scientist vs data engineer

Data Scientists can sometimes be presented with large data without a particular business problem in mind. In this case, the curious scientific data should explore the meaningful data, find the right quetions and provide interesting results. This is tricky because, to analyze the data, an expert Data Scientists should have a very wide knowledge of the different techniques of automatic learning, data mining, statistics and large data infrastructures.

Data Scientist should have the experience of working with different datasets of different sizes and shapes, should be able to run its algorithms on large data efficiently . This is why it is essential to know the fundamentals and computer programming, including the experience of languages ​​, databases (large / small) technologies.

 Competencies and tools:

Data analysts must have a basic understanding of some basic skills: statistics, data   munging,  data visualization, data analysis, Microsoft Excel, SPSS, SPSS Modeler, SAS, SAS Miner,  Table, SSAS.

 Who  is  DATA   ANALYST:

“A  software   engineer  with a good understanding of mathematics and statistics “.

Data analysts are experienced professionals in their organization who can query and process data, provide reports, summarize and visualize data. They understand how to use existing tools and methods to solve a problems, help people across the company understand specific queries with ad hoc reports, graphs.

DATA ENGINEER:

Data engineers are struggling with the challenges of integrating databases and large unstructured datasets. The conclusive   goal of a data engineer is to provide own data in a format usable to data analysts, data scientists or anyone who   needs  it. To summarize, data engineers are geeks of data that lay the foundation for data scientists to easily work with  necessary data, for their calculations and experiments.

data scientist vs data engineer

 TASKS TO BE DONE BY THE ENGINEERS:

Build and maintain highly expandable database management systems.

Suggest   various   techniques   to enhance the data reliability, data efficiency and data speed quality.

Develop  Designs  specialized to user defined functions and analytics applications.

 KEY SKILLS OF A DATA ENGINEER:

Data Warehousing

Design Database

Data collection and transformation

Coding.

   GROWTH RATE IN DATA SCIENCE FIELD ACCORDING TO THE JOB TITLE

data scientist vs data engineer

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