Before going through what Big Data is, let us have a look at some powerful stats.
- It is expected that the global datasphere will grow 175 zettabytes by 2025.
- The Big Data industry, as estimated, will reach USD 77 billion by 2023.
- Today, Big Data is utilized by nearly every industry. As far as predictive analysis is concerned, the media and entertainment industry is on the top.
- The banking sector generates exceptional amounts of data. By 2021, the amount of data generated every second in the finance industry is expected to grow by 700%.
- A majority of enterprises are trying to store their data in public cloud data warehouses such as Amazon Redshift, Snowflake, and Google Big Query, and it will be done by 2023.
- According to Statista, the Big Data and business analytics market has reached USD 169 billion in 2018 to USD 274 billion in 2022.
- Another report by Datafloq states that Big Data revenues are expected to grow up to USD 123.2 billion by 2025.
What do you notice from the stats mentioned above? It is that Big Data is everywhere, in every industry, and is only going to grow, opening doors of opportunities for a bright career in Big Data. This has brought a surge in the candidates opting for a career as a Big Data Engineer.
What is Big Data?
Big Data is a term that describes huge volumes of data that includes structured and unstructured data. Big Data inundated a business on a daily basis. The data is so huge that it is termed “Big Data” and is so large, fast, and complex that it is impossible to process it using traditional methods.
One thing to be noted is that it is not the amount of data that is important, but the thing that matters is how and what organizations do with the data. Typically, Big Data is analyzed to gain meaningful insights that lead to better business decisions and strategic moves.
The mainstream definition of Big Data, articulated by the industry analyst Doug Laney in 2000, is the three V’s.
Volume: Organizations gather data from different sources, including smart IoT devices, business transactions, videos, social media, industrial equipment, and many more. Traditionally, it would have been challenging to store this data, but proper storage on platforms like Hadoop and data lakes has made the storage easy.
Velocity: With the exceptional growth in IoT devices, data enters into businesses at an incredible speed and must be handled conveniently. Sensors, smart meters, and RFID tags(Radio Frequency Identification) drive the requirement of dealing with these torrents of data in close real-time.
Variety: Data occurs in all types of formats- from numeric, structured, in traditional databases to unstructured text documents, videos, audios, emails, stock ticker data, and financial transactions.
The two additional dimensions that are described these days are variability and veracity. The flow of data is unpredictable and is varying greatly. Veracity is all about the quality of data. Since data comes from a variety of sources, it’s difficult to cleanse and transform the data across systems.
Different frameworks like Spark, Cassandra, Hadoop, and Apache Storm are used to overcome the challenges that come across processing Big Data. With the help of these frameworks, a Big Data Engineer can handle all of this Big Data. Let us now explore what a Big Data Engineer is and how to become one.
Who is a Big Data Engineer?
As it is one of the most in-demand job roles today, this is the best career option for candidates who are inclined towards making a career in big data. A Big Data Engineer is a professional who develops, maintains, tests, and evaluates an organization’s Big Data infrastructure. As a Big Data Engineer, you process the data in such a way that it results in benefits and growth for your organization.
As a Big Data Engineer, some of your responsibilities are:
- Design, develop, build, install, test, and maintain the complete data management and processing system.
- Develop highly scalable, fault-tolerant, and robust systems for ingestion and data processing.
- Perform Extract, Transform, and Load (also called ETL) operations.
- Make sure that the architecture planned meets all the business objectives. You are required to generate structured solutions by integrating various programming languages and tools.
- Identify various opportunities for data acquisition and explore different ways of utilizing existing data.
- You are also required to propose new ways of maintaining the quality of data, its reliability, and efficiency as well.
- Deploy disaster recovery techniques.
- Perform data mining to collect data from various resources to develop efficient business models.
- You are also required to work with data analysts and data scientists.
The Dice 2020 Tech Job Report states that Big Data Engineer was the fastest-growing job in IT with year-over-year growth of 50% in the number of open positions.
Compensation
The average annual salary of a Big Data Engineer in India is around INR 8,56,643 and varies with factors such as geographic location, company size, reputation, job position, educational qualifications, and work experience as well. Some of the companies hiring Big Data Engineers paying high compensation are Airbnb, Google, Amazon, Spotify, Netflix, IBM, Accenture, Deloitte, Capgemini, and many more.
The steps to follow to become a Data Engineer are:
Get your graduation degree, and acquire skills such as operating systems and programming, SQL and DBMS, Hadoop and Spark Frameworks, ETL and Warehousing Tools, Data Mining and Modelling. The final step is to earn a Big data Engineer Certification that can make you land your dream career.
Conclusion
Big Data is everywhere today, and all the transformations in the digital world today are accomplished with Big Data.
To become a Big Data Engineer, which is the most in-demand job role in the current IT world, the best way is to go with an online training course. With hands-on practice with real-life projects and training through industry experts, it is sure that you will earn the certification without any trouble.
Enroll yourself now!