Data science and data analytics are growing at a very high speed, and companies are now looking for professionals to filter through the data gold mine and help them make fast and efficient business decisions. IBM forecasts that the number of vacancies for all data professionals in the US will increase from 364,000 to 2,720,000 by 2020. To find out what science is we met Eric Taylor, the Senior Data Scientist working at CircleUp, in a Simplilearn Fireside. 

This article covers the following topics, which will give you a clear understanding of the meanings, differences, and skills needed to become a scientist and data analyst, as well as more topics in detail, including:

• What is data science?
• Major skills that are requisite to Become a Data Scientist
• What does a Data Scientist do?
• What is data analysis?
• Skills that are requisite to Become a Data Analyst
• What does a Data Analyst do?
• Difference between a data science and a data analysis

What is data science?

People have been trying to explain data science for over a period of 10 years, and the best way to answer the question is with a Venn diagram. This Venn Diagram was created by Hugh Conway in 2010 and consists of three circles: math and statistics, technical competence (knowledge of the domain to be summarized and calculated), and hacking skills. In essence, if you can do all three, you are already well versed in data science.

Data science is a concept against big data and includes data cleaning, preparation, and analysis. A data scientist collects data from various/vast sources and applies predictive analytics, machine learning, and sentiment analysis to bring out critical information from the collected datasets. They understand data from a business perspective and can provide accurate forecasts and information that can be used to make important business decisions.

Skills Required to Become a Data Scientist

Anyone looking to build a solid career in this area must develop essential skills in three departments: Analysis, Programming, and Domain Knowledge. If you take it a step further, the following skills will help you find a niche for yourself as a data scientist:

• Good knowledge of Python, Scala, SAS, R
• Hands-on experience in coding SQL databases
• Ability to work with unstructured data from multiple sources such as video and social media
• Understand various analytic functions
• machine-learning knowledge

What does a data scientist do?

A data scientist will generally be more involved in outlining data modeling processes, designing algorithms and forecasting models. As a result, data scientists can spend more time designing tools, automation systems, and data structures.

Comparatively a data scientist may be more concentrated on developing new tools and methods to pull out the information the business needs to resolve compound problems than a data analyst. It’s also good to have business instinct and critical thinking skills to understand the entanglement of the data. Some in this field might recount a data scientist as someone who not only has hacking skills but also math and statistics to approach problems in new ways.

What is data analysis?

A data analyst is generally the person who can create basic descriptive statistics, visualize data, and communicate data points to wind up. You should have a basic knowledge of statistics, a perfect command of databases, the ability to create new views, and insight into data views. Data analysis can be seen as the necessary level of data science.

Skills Requisite to Become a Data Analyst

A data analyst must be able to answer a specific question or topic, discuss what the data looks like, and present it to relevant stakeholders across the organization. If you want to become a data analyst, you need to learn these four key skills:

• knowledge of mathematical statistics
• Good understanding of R and Python
• Data dispute
• Understand the PIG/HIVE

What does a data analyst do?

A data analyst generally gathers data to recognize trends that will be helpful to business leaders to make deliberate decisions. The adherent focuses on performing statistical analysis to answer questions and resolve problems. A data analyst uses tools like SQL to query relational databases. A data analyst can also clean the data or put it into a usable format, remove irrelevant or unusable information​​or figure out how to deal with missing data. For more details Visit Data Science Training in Hyderabad

A data analyst usually works as part of an interdisciplinary team to find out business goals and then manages the data extraction, cleansing, and review process. The data analyst uses programming languages ​​like R and SAS, visualization tools like Power BI and Tableau, and communication skills to develop and communicate their results.

Data science vs. Data analysis

• Data science is a wide-ranging term that encloses data analysis, machine learning, data mining, and many other related subjects.
• While a data scientist is supposed to forecast the future based on past patterns of the earlier, data analysts pull out important information from a diversity of data sources. 
• While a data analyst finds answers to already existing questions, a data scientist raises questions.