There is the difference between data scientist job, big data specialist job, and the data analyst. Data scientist need to know the python coding, data analysis, and the Hadoop knowledge. The big data specialist should know the analytical and statistical skills, data analyst need to know the programming knowledge as well as the statistical skills. As the data is growing from the gigabytes to megabytes the need for processing the data to understand the big business is inevitable. A small business uses excel and oracle whereas big business use excel, Hadoop and data science for the data analysis. Data scientists deserve good salary growth when compared to the Hadoop engineers. Join the Hadoop Training in Chennai to become a successful Hadoop engineer. Let me discuss in detail how the job role of Hadoop engineers and data scientists differs in the companies. Here is the article on Difference between the Hadoop engineer and the database scientists
The Job responsibility of a Hadoop engineer
- The Hadoop engineer checks the data source. The data source can be through the RDBMS or log files or internet or through an intranet. The data can be structured data or unstructured data.
- Understand the various formats of data like JSON-text format or XML-text format or data from the internet. HTML and XML are used to display the data and store the data. Hadoop Training Chennai is the best course for the beginners to get their dream job.
- Use the ETL or ELT to clean and test the data. ETL tool associated with Hadoop are pig, spark, and hive. Big Data Training with the practical approach from the experienced trainers provides in-depth knowledge.
The Job responsibility of data scientist:
- The data scientists analyze the semantic search technology. The semantic search is about using the boolean search or the query to the database. It matches the data, content and the software program code at design time. Data science training and the Big Data Training in Chennai prepares the professionals for the future jobs.
- Data scientists decide about the algorithm for the machine learning, a framework to be applied and tools to be used for the data analysis.
- After the data analysis, they prepare the PPT to explain the management regarding the result of the data analysis.
Future of Hadoop and data science
Data scientists are required in the advertisement industry, financial services, and retail industry etc. Hadoop engineers are required in travel, healthcare, energy management and gaming industry etc. The big data or Hadoop is for coding and using the Hadoop and spark tools. Most of the companies use big data and Hadoop. The skills required for Hadoop engineer are R programming, SAS knowledge, and the python knowledge. Hadoop engineer should have the storytelling skills, designing, good decision maker, R knowledge and the tools knowledge. The data scientists profile demand for the skills like good reasoning, problem-solving skills, creative and proactive, curious to hacking mindset, influence the management, and understand the marketing trends. To manage the competition in the different sector the wide usage of the data analysis is important. By the year 2020, there will be $430 billion increase in the productivity and the growth of the data.
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