COMPARISON OF DATA SCIENCE EXPERTS

The most recent industry predictions claim that within 2020, 28% of all digital jobs will be made up from the field of Data Science. This means an extraordinary demand for all categories of Data Science professionals. But there is some confusion regarding the categories of professionals here. In this article, we discuss the comparative status of data scientist vs data analyst vs data engineer.

Skill-sets

The skill-sets vary with each category of Data Science expert. The role of a Data Analyst is the least technical of the three categories. Since this is an entry level position, the Data Analyst needs to be able to skillfully use tools, such as, Microsoft Excel, SPSS, SSAS and SAS Miner. Additionally basic competence with R, Python, SQL, SAS and JavaScript is a distinct advantage. 

The Data Engineer needs to have strong expertise in the use of Programming Languages like Java, SQL, Python and SAS. Frameworks such as Hadoop, Pig, Hive, Apache Spark, NoSQL, Data Streaming, MapReduce etc are part of the essential Skill-set of the Data Engineer. 

The Data Scientist must have mastery over a number of Programming Languages which he /she should be able to use interchangeably or as required. Some of these are R, Python, Java, SQL, SAS and so on. Big Data Frameworks, like Hadoop, Spark and so on, must be completely mastered by the Data Scientist. The latest technologies such as Machine Learning and Deep Learning, should be at the Data Scientist’s beck and call.  

Responsibilities

The responsibilities of a Data Scientist are generally as follows:

  • Dealing with unstructured data, by mining and cleaning in order to prepare it for practical use.
  • Creating models for Big Data operations.
  • Analyzing and Interpreting Big Data.
  • Playing the Leadership role for the data team, and assigning and guiding towards goals.
  • Delivering impactful solutions and results for the business.


The Data Engineer is on the middle rung of the ladder, and his responsibilities are accordingly:

  • Conversion of erroneous data into a practical and usable form for data analysis.
  • Preparing queries on the data.
  • Data mining to extract insights.
  • Data Design and Architecture maintenance.
  • Using ETL (extra transform load) technology to develop large data storage and warehousing.

As a comparative newcomer to the Data Science scene, the Data Analyst also has specific responsibilities, which are:

  • Using Databases to collect information with the queries prepared by the Data Engineer.
  • Assist in data processing and result summarization.
  • Utilize the basic algorithms for data preparation using linear regression, logistic regression, and others.
  • Display expertise in data mungling, data visualization, initial data analysis and statistical evaluation.

Job Description and Earnings

The Data Scientist is the senior-most in the Data team, followed by the Data Engineer, who is his assistant, and looks after the nitty-gritty, and is supported by the Data Analyst. The earnings are also obviously in descending scale, but they belong to the highest in the industry. 

This concludes our study of data scientist vs data analyst vs data engineer. 

Datamites institute is offering data science course in Bangalore, Chennai, Pune and Mumbai. If you are data science aspirant then join Datamites and get certified.


Comments

Post a Comment

Popular posts from this blog

9 Skills You Need to Become a Data Modeler in 2021

What is data modeling, and what are its effects? Data modeling computes how an organization manages the data flow in and out of the database management system. Because it is responsible for making space needed for your data, data modeling is one of the most critical parts of a large data project. Modeling data structure space for your data and maintaining factors related to your data environment live in the run. In short, data modeling is data management in an organization. Decisions regarding data modeling require early access to data collection. It's up to the organization to decide what story will be told by every data to be said, and for the data to inform the perfect level, it needs to be modeled perfectly. Many software applications utilize the data modeling process to provide the most seamless customer experience. With a culture that changes the world, the data you hold must change in the way that best suits the final customer's needs. Ensuring the perfect customer exper
Read more

Why DataMites Institute for Data Science Course in Pune

Image
Data science is a rapidly growing field that has seen an increasing demand for skilled professionals in recent years. With the IT industry booming in Pune, there is a huge demand for data scientists who can help businesses gain insights and make data-driven decisions. If you are looking to pursue a career in data science, choosing the right institute is crucial. In this article, we will discuss why DataMites Institute is an excellent choice for a data science course in Pune. DataMites Institute is a leading institute for data science courses in Pune . The institute offers a comprehensive data science curriculum that covers all the essential concepts and tools required for a successful career in data science. The institute's courses are designed to equip students with the latest skills and knowledge in data science, machine learning, and artificial intelligence. If you are looking for Data Analytics Course in Pune . Now, DataMites is providing data analytics training. One of the key
Read more

4 Types Of Data Analytics To Improve Decision-Making

 Suppose you are on the CSE Stack portal. In that case, there is a good chance that you already know well with general terms such as 'data analytics,' 'big data,' and 'business intelligence leads to various things in different circumstances. But do you think what will be the right BI platform to hack several solutions to business success? In this article, we will criticize the term 'analytic data' by breaking it into four different types and harmonizing it with the aim of decision making. Descriptive Analytics: What happened? The most common types of general analysis, descriptive analytics, offer a comprehensive view analyst on the metrics and main steps in an organization. It analyzes available data in real-time and historically to gain meaningful insights into the future of a company. The main objective of this primary type of analysis is to find reasons behind magnificent successes or failures in the past.  Diagnostic Analytics: What makes it happen? Afte
Read more