Data brings all arguments to a level. As Sherlock Holmes said, " The temptation to form premature theories upon insufficient data is the bane of any profession." The business world has taken this quite seriously now. The data science field is hot as lava, and there are doubts that it will ever subside soon.The increased focus by companies on acquiring data science talent resulted in the creation of whole new data roles and titles. With the behemoths of positions and job postings in the various site, proper differentiation of each function is reasonably necessary.
Data Scientist: Can be branded as a rare unicorn; they have a mindset of curious data wizards. Their role is to clean, organize and manage all the collected data. The language prerequisite is of R, SAS, Python, Matlab, SQL etc. The significant skills required are knowledge of predictive modeling, maths, stats, and machine learning. Google, Mocrosoft & Adobe hires them
Data Analyst: A role that can identify a data detective with a high “figure it out” quotient. The major function in this role is to collect, process and perform data analysis on the data set. The languages requirement includes R, Python, HTML, Javascript etc. The important skills required are predictive modeling, maths, stats, machine learning, and spreadsheet tools and database systems. IBM, HP & DHL hires them
Data Architect: A contemporary data modeler, this role needs an inquiring man with love for design patterns. The primary functions includes creating blueprints for data management systems to integrate, centralize, protect and maintain the data sources. The languages requirement includes SQL, XML, Hive, Pig, Spark etc. The skills requirements include data warehouse solution, knowledge about data structure, extraction transformation load (ETL), spreadsheet and BI tools and system developments. VISA, Cocacola & Logitech hires them
Data Engineer: A software engineer by trade, this rle can be termed as a “all-purpose everyman”. The role requires developing, constructing, testing and maintaining architectures. The languages requirement includes SQL, Hive, Pig, Ruby, C++ etc. The skill requirement is of a database system, data modeling, data APIs, data warehousing etc. Spotify, Facebook & Amazon hires them
Statistician : Also known as " historical leader of data" the mindset of logical and enthusiastic stats genius is required. The role requirement is to collect, analyze, and interpret qualitative and quantitative data with statistical methods and theories. The languages requirement includes R, SAS, SPSS, SQL, Stata etc. The skills needed are data mining and machine learning, distributed computing and database system. Linkedin, Johnson & Johnson & Pepsico hires them.
Database Administrator: Also called as a database caretakers, they are the preventers of disasters, with a role to ensure that the database is available to all relevant users and keep the data safe and properly working. The languages requirement includes SQL, Java, XML, C#, Python etc. The skills needed here are backup and recovery, data security, distributed computing, ERP & business knowledge etc. Tableau, Reddit & Twitter hire them.
Business Analyst: Branded as change agents, they have to be resilient project jugglers. This role requires improvement of business processes and intermediary between business and IT. The languages requirement includes SQL. The skills needed are basic office tools, business intelligence understanding, data modeling, conscious listening and visualization skills. Uber, Dell and Oracle hire them.