There is a difference between a Data Scientist job, a big data specialist job, and a data analyst. Data scientists need to know Python coding, data analysis, and Hadoop knowledge. The big data specialist should know analytical and statistical skills, and data analysts need to know programming knowledge as well as statistical skills. As the data is growing from gigabytes to megabytes, the need for processing the data to understand big business is inevitable. A small business uses Excel and Oracle, whereas big business use Excel, Hadoop and data science for data analysis. Data scientists deserve good salary growth when compared to 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 the 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 the internet, or 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 Online Training is the best course for beginners to get their dream job.
- Use the ETL or ELT to clean and test the data. ETL tool associated with Hadoop is pig, spark, and hive. Big Data Training at FITA Academy, with the practical approach from experienced trainers, provides in-depth knowledge.
The Job responsibility of a 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 software program code at design time. Data science and Big Data Training in Chennai prepare professionals for future jobs.
- Data scientists decide about the algorithm for the machine learning, the framework to be applied, and the tools to be used for the data analysis.
- After the data analysis, they prepare the PPT to explain to the management the result of the data analysis.
Future of Hadoop and Data Science
Data scientists are required in the advertisement industry, financial services, retail industry etc. Hadoop engineers are required in travel, healthcare, energy management and gaming industry etc. Big data or Hadoop is for coding and using the Hadoop and spark tools. Most companies use big data and Hadoop. The skills required for Hadoop engineers are R programming, SAS knowledge, and Python knowledge. The Hadoop engineer should have storytelling skills, designing, good decision making, R knowledge and tools knowledge. The data scientist’s profile demands the skills like good reasoning, problem-solving skills, being creative and proactive, having a curious hacking mindset, influencing management, and understanding marketing trends. To manage the competition in the different sectors, the wide usage of data analysis is important. By 2020, there will be a $430 billion increase in productivity and the growth of the data.
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