Data Science, The Field of Smart Study

Data Based Science, the Field of Study :-

Data Analyst

   Data Science is a multi-disciplinary field that uses scientific methods, processes, algorithms and systems to extract knowledge from structured and unstructured data.

  Data science has different fields e.g., mathematics, statistics, machine learning, cluster analysis, big and small nano data analytics, data visualization, artificial intelligence, neural networks, deep learning, computer database and so on. 

The Data Scientist:-    The Data Scientist is probably one of the best job titles that you can put on your business, and the closer you get to silicon valley. 
     Languages:- 
  R, SAS, Python, Matlab, SQL, Hive, Pig, Spark. 

   Skills:- Distributed computing, Predictive modeling, story telling and visualizing, Mathematics, statistics and machine learning.

The Data Analyst:- 

    Languages- R, Python, HTML, JavaScript, C++, SQL. 

   Skills:- Spreadsheet tools, Database systems, Communication and Visualization, Mathematics, statistics and machine learning

Data Analytics

   The Data Architect:- 

   Languages:- SQL, XML, Hive, Pig, Spark. 

   Skills:- Data warehousing solution, In-depth knowledge of database architecture, Extraction transformation and load, Spreadsheet and Bl tools, Data modeling, system development. 

   The Data Engineer:- 

  Languages:- SQL, Hive, Pig, Matlab, SAS, SPSS, Python, Java, Ruby, C++, Perl. 

    Skills:- database system, data modeling, data API's, Data warehousing solution .

Data Statistics

The Statistician:- 

Languages: R, SAS, Matlab, Stata, Python, Perl, Hive, Pig Spark, SQL. 

 Skills: statistical theories and methodology, Data mining and ML, Distributed computing, Database systems, Cloud tools. 

The Database Administrator:-

Languages: SQL, JavaScript, Ruby on Rails, XML, C#, Python. 

Skills: Backup and recovery, Data modeling and design, Distributed computing, Database systems, Data security, ERP and business knowledge. 

The Business Analyst: 

Language- SQL 

Skills: Basic tools (e.g., MS office), Data visualization tools (e.g., Tableau), Conscious listening and storytelling, Business intelligence understanding, Data modeling. 

Data & Analytics Manager: He/She steers the direction of the data science team and makes sure that the right priorities are set. 

Languages: SQL, R, SAS, Python, Matlab, JavaScript. 

Skills: database systems, leadership and project management, interpersonal communication, data mining and predictive modeling. 

Source:- 

1. Journal of Data Science 

2. Journal of the Statistical Association

3. Wikipedia