149 zettabytes

This is the volume of data that would be created across the globe by 2024.

Big Data and Analytics Software revenue across the world in 2019 reached a whopping USD 69 billion.

Within the next five years, there will be around 50 billion smart connected devices, all meant to collect, analyze, and share data.

Less than 0.5% of all the data that is generated is analyzed and used.

The rate at which data is generated across the globe and our ability to analyze it is growing; businesses of all sizes and types will be using one or the other form of data analytics to influence their business in the coming years. 

Also, the global big data and data engineering service market is anticipated to grow from USD 32.45 billion in 2017 to USD 123.89 billion by 2025, at a Compound Annual Growth Rate of 18.2%.

Now when everything has gone data-driven, more and more companies are looking for qualified individuals with appropriate data and IT backgrounds.

Eventually, this will increase the demand for data engineers and big data developers in almost every corner of the world. Certification in Data Engineering can help you make your career in this domain. Generally, the aspiring candidates look for data engineer courses as they serve the purpose of launching a bright career in the ever-growing field of Big Data.

Let us now have a glance over what is a Big Data Developer and how to become one.

What is Big Data?

Simply put, Big Data is a term used to refer to huge datasets. These huge datasets are required to be computationally analyzed to convert them into a format that is readable and understandable. These huge datasets contain sensitive information and can reveal trends, associations, patterns, and other meaningful aspects that can help businesses in better performance.

Who is a Big Data Developer?

A Big Data Developer is required in a company to analyze Big Data properly. a Big Data Developer is responsible for delivering an array of data-related IT services. You are required to work with Big Data frameworks and components such as Hadoop, Hive, and MapReduce that allow the users to interpret information, debug and optimize data, and oversee other significant responsibilities. Developing Hadoop applications serve the purpose of solving Big Data issues and requirements. 

Role of a Big Data Developer

Design, develop, install, configure, and control Hadoop applications.
Maintain data privacy and security.
Propose best practices and solutions.
High-speed data querying.
Manage and deploy Hbase.
Build scalable and high-performance web services that help in tracking data.
Perform appropriate analysis of large data sets.
Translate complex functional and technical requirements into detailed design.
Propose changes in design and suggestions to different processes and products.

Since a Big data developer has a lot of responsibilities, to become one you should acquire a certain set of skills and inculcate them into your performance.

Skills Required to become a Big Data Developer

1. Excellent knowledge of Big Data Frameworks

Because you have to work with Big Data all the time, it is crucial to have an in-depth knowledge of Big Data frameworks, specifically, Hadoop. Hadoop is such a framework that stores and processes data in a distributed environment and allows for parallel processing. Hadoop forms the foundation of other Bug Data technologies. Learning the Hadoop ecosystem, which contains different tools for different functions, can prove to be a stepping stone towards mastering Big Data Development. The Hadoop ecosystem includes HDFS, YARN, Hive, Flume, MapReduce, Pig, etc.

2. Knowledge of Real-time Processing frameworks

Apache Spark, known for excellent performance when it comes to real-time processing, is really essential to learn for Big Data development. Real-time processing is required for almost all the functions such as recommendation systems or fraud-detection systems. Since Apache Spark is prevailing today as a real-time processing framework, it is crucial for you to master the concepts involved in the framework.

3. SQL-based Technologies

SQL or Structured Query Language is a data-centered querying language that is used to arrange, manage, and process the structured data stored in data repositories. To work with Big Data technologies, you need to learn SQL thoroughly.

4. NoSQL-based technologies

Since most of the data generated are unstructured, it is equally important to learn NoSQL based technologies. The amount of data generated by our activities over the Internet is growing exponentially, making it essential for organizations to process unstructured data as well. To meet the requirements of processing this huge amount of unstructured data, you need to learn NoSQL (Not Only Structured Query Language) technologies as well. 

Some of the popularly used NoSQL-based techniques are Cassandra, MongoDB, Hbase. 

5. Programming Languages

It is impossible to stay in the IT world without learning the basic programming languages. You must have a sound knowledge of data structures, algorithms, and any of the popular programming languages such as R, Java, Python, Scala, etc. that caters to Big data development purposes.

6. Data Visualization Tools

Knowledge of some prominent data visualization tools like Tableau and Qlikview can help you brush up your analytical and data visualization skills. These tools can help you easily understand complex data sets with creativity and attention.

7. Knowledge of Operating Systems

The most widely used operating systems are Unix and Linux. You need to master any of these to launch a career in Big Data Development.

8. Machine Learning

The knowledge of machine learning is crucial as it helps in creating classification systems, personalization, and recommendation systems. Now when the technology is advancing at an exponential rate, the professionals with prescriptive analysis and predictive analysis skills are an added advantage. 

Apart from the skills mentioned above, you are also required to develop statistical and quantitative analysis, business knowledge, creativity, and critical thinking. 

Salary of a Big Data Developer

The average annual salary of a Big Data Developer in the US is around USD 87,321, according to PayScale. The salary increases with an increase in experience level added certification, and other factors. 

Bottom Line

It is obvious that making a career in Big Data can place you in a secure job role and that too with great salaries. To receive adequate training in Big Data and take an exciting step towards a career in Big Data, enroll now into an accredited training institute. It provides the appropriate knowledge required to excel in this field.