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 Role of Hadoop In Data Professional’s Life

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Stepping in the 21st century still the perfectly defining statement for a data professional is weird. Data Professional can be narrowly regarded as Data Scientists, Data Analysts, and Data Engineers but we have to take a note that these three terms may sound very similar but they don’t define a similar output. In the closest definition it can be regarded as a data professional who focuses more often on building data pipelines, structures, and manages to make the data travel from point A to point B is a Data Engineer. Hadoop

While a data professional who is more oriented to towards producing reports and describing trends and insights in the data as a data analyst. Further data scientist can be defined as a person who is professional in data and focuses on producing more insights and future predictions of the data. Conclusively, there is plenty of differences in the roles of data professionals yet its fuzzy and important one.

Role of Hadoop In Data Professional’s Life

Typically professionals who are more specialized and have comparatively more skills and expertise are the data scientists than the data analysts. While data engineers might have much more knowledge in databases but they are incompetent in statistics. So field has not achieved a point where an individual can comment easily and determine the overall extent of the data professional’s role by just reading the title. 

Big Data Analytics Training is a certification awarded to the data professionals who have the ability to manage and understand the mountains of data and create a solution out of the data. But all above mentioned tasks done by data professionals requires high amount data for execution and lots of storage to work with. Hence in later times Data is the key to every lock of industry, in just past 2 years 90 percent of total useful data is created, due to this factor organizations are sitting on mountains of data now and they are very unsure of the fact that what they actually want to do with the data. Therefore data professionals come into play, the industry needs them to understand this data and make sense at all out of it.

In a recent survey by Paradigm4, it is found that nearly 49% of Data Professionals either use Spark or Hadoop for data preparation or management. And it is almost an industry standard to learn Hadoop for the execution of the data. Normally a data scientist’s job is not to build clusters or administer a Hadoop cluster but they require Hadoop for gleaning valuable insights from the data regardless of where the data might becoming. Data scientists normally prefer technical skills like Spark, Hadoop, NoSQL, Python, Java, and more. Out of all these Apache Hadoop is the most prevalent technology and is the most essential skill for a data professional. People are taking up Hadoop Training to upskill in this stream and start a career in Big Data.

How Hadoop helps in Data Science or in a Data Professional Career?

Suppose if a job can be done in 20 minutes to execute, considering the same size of a job it can be completed in 10 minutes if the computers are doubled. It might not matter that much in a small scale but in large scale it plays a very important role. Data scientists can first load the data into Hadoop then can question regardless of the scheme of the dataset they are working in. Hence data scientists can just relax without having that anxiety or stress to of doing any transformations in order to get the data into the cluster. The Most important aspect for a data professional is they must be expert in working with the distributed system of data with Hadoop for data science. Without having to get with inter-process communication, message-passing, network programming, etc. Hadoop provides a brilliant system of parallelism as data professionals just have to type a Java based MapReduce code for using other big Data tools like Hadoop that they are taught while getting the Big Data Training.

Features of Hadoop that helps Data Professionals

Hardoop for Data Exploration

Hadoop helps data professionals in figuring out the complexities in the data and also helps in storing the data as it is.

Hadoop for Filtering Data 

In Hadoop, a data professional can filter a subset of data easily and solve a specific business problem.

Hadoop for Data Sampling

Sampling the data gives a data scientist a clear idea on what to approach that will work or might not work for modeling the data. Hadoop Pig has a very cool keyword ”Sample” that helps a lot to trim down the number of records.

Hadoop for Summarization

MapReduce in Hadoop helps to summarize the data as whole and helps the data professional in getting a bird’s eye of better building data models.