A – Z Guide on becoming a Successful Big Data Engineer

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What is big data?

Big Data is a domain that treats way to monitor, thoroughly extract information from the large or complex application software. This method is used to access data which cannot be managed by traditional style of data-processing.  It is normally used by large organization to extract big data via diverse sources. The organization collects data through transactions, applications, leads, videos, content etc.

It is very important to understand how a company utilize the data for their development. They have to analyse entire process and extract the useful stuff from the entire process.

There are 4 Vs. for Big data, which helps you to understand this quickly.

Volume: The big data is a collective form of structured and unstructured data gather by company through diverse sources. Thus the volume of data describes whether it is a big data or not.

Variety: Variety come through different sources, thus it comprises of some useful data.

Velocity: As the mobile devices are increasing day-by-day, data storage is all necessary and at the same time it is important to manage it and take all the possible advantage from it.

Big Data Veracity: It refers to the quality of data a company have. We have to analyse the quality of data and reliability.

Why is a big data engineer important to an organization?

A big data engineer is very important for any organization like data scientist. In today’s world with the endless data a data engineer has the power to simplify the complex data into understandable form. Now day’s companies have lots of data but they don’t know how to utilize it because it is in raw form.

Big data engineers extract the unwanted things, arrange the data, design it in appropriate form, increasing its quality, reliability and efficiency and then present it further to data scientist to convert that data into a pure form. So basically big data engineers construct a bridge between big data and data scientist and make them sure that not even one obstacle remain on the way.

In Big Data number of data are kept in an isolated form and those data is been accessible by our engineers. Sometimes data scientist cannot perform all these task, thus they need data engineers to perform these activities.

Works of big data engineers?

They design a structure of informative and useful data from complex data structure and do ETL (Extract, Transfer and Load) process with big data to make it easier for further use. They also save the data in different section on the basis of their variations to find it easily later and also perform lots of other works.

Skills required:   

Apache Hadoop: This tool first launch in 2012 basically a open source network of some software which allows you to store and analyze big data. The storage part of hadoop is called HDFS ( Hadoop Distributed File System). A big data engineer must have knowledge of this tool, this tool divide a big data in numbers of small modules and save it safely.

MapReduce : On the basis of name we can also assume the work of this software, it may be work like distance cutter of similar files or useful files. Now let’s go through the real definition, it is software which place files in parallel queues on the basis of similarities of files for quick availability. This software also accessible through Hadoop tool.

Data Streaming: If you are or want to be a big data engineer, you should know data streaming. It is the process of continuously running data on high speed rather than download it at a time. Now when we have broadband internet, 4g networks we stream more data and a company stores more data. A data engineer have to analyze data at the time of streaming.

Programming: Basically they work on the simple method of engineering and architecture, they design the data and create a flow method but at many places they have to reprogramming the language for change their aspects. So it is very important to have high knowledge of programming language, after that you can analyze the data.

SQL: It stands for Structured Query Language, it is very important in managing and handling data. We can find out the queries and solve it with the help of this language.

Focused and Disciplined: The big data engineering is a challenging job, they have to analyze huge scale data and it increases continuously and rapidly, so to cope up with that you want discipline. At data streaming time you are liable to find out unwanted data, arrange it at the same time, you should have a proper focus on your work.

Courses:

There are many universities Syracuse University, University of Denver, University of California, American university, University of Dyton, Pepperdine University. These universities provide course online who want to be a data engineer can apply here.

You also can learn this by practical knowledge by taking projects and join an internship, and this is the best way to explore anything. Practically we fight with all issues and learn better.

Salary Package:

Now all companies work on internet basis and have a huge data structure and they really want to get leads and possible profits from these data. As result they hire data engineers.

The requirement of data engineers is very high but the professional who have practical knowledge are very low. So you have a great chance to boost your career in this field.

The salary of individuals is depends on their skills and company but the average salary in India is 8,00,000  Rs per year. With the improvement in your skills the salary increases, many of data engineers earns several lakhs of month.

So this is a great choice, and if you like my blog or this is helpful to you please share it with others to help others, who thinks about their future career strategies.

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