Generally, we hear different designations about CS Engineers like Data Scientist, Data Analyst and Data Engineer. Let us discuss the differences between the above three roles.
- Data Analyst – The main focus of this person’s job would be on optimization of scenarios, say how an employee can improve the company’s product growth. Data Cleaning and organizing of raw data, analyzing and visualization of data to interpret the analysis and to present the technical analysis of data.
Skills needed for Data Analyst are R, Python, SQL, SAS, SAS Miner.
- Data Scientist – The predominant focus will be on the futuristic display of data. They provide both supervised and unsupervised learning of data, say classification and regression of data, Neural networks. The continuous regression analysis would be using machine learning techniques.
Skills needed for Data Scientist are R, Python, SQL, SAS, Pig, Apache Spark, Hadoop, Java, Perl.
- Data Engineer – Data Engineers concentrate more on optimization techniques and building of data in a proper manner. The main aim of a data engineer is continuously improving the data consumption. Mainly a data engineer works at the back end. Optimized machine learning algorithms were used for maintaining data and to make data to be available in most accurate manner.
Skills needed for Data Engineer are Pig, Hive, Hadoop, MapReduce techniques.
- Difference between a Data Analyst and a Data Scientist
- Difference between Data Warehousing and Data Mining
- Difference between Data Warehouse and Data Mart
- Difference between data type and data structure
- How to Become a Data Scientist in 2019: A Complete Guide
- How to Become a Data Analyst in 2019: A Complete Guide
- How Big Data Artificial Intelligence is Changing the Face of Traditional Big Data?
- Types of Sources of Data in Data Mining
- Difference between Stack and Queue Data Structures
- Difference Between High-level Data Link Control (HDLC) and Point-to-Point Protocol (PPP)
- Difference between Row oriented and Column oriented data stores in DBMS
- Difference between Structured, Semi-structured and Unstructured data
- Difference between Linear and Non-linear Data Structures
- 5 V's of Big Data
- Big Challenges with Big Data
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