2020, a blockbuster year for “Big Data.”
90% of the world’s data have been created within a span of two years. Nearly 2.5 quintillion bytes of data are being generated daily, so says an IBM report.
With such data that keeps generating every second, it is evident that more and more companies will be needing big data analytics and professionals to help expand their businesses
Due to the huge demand, software developers are now planning to switch their career into the big data space. Big data engineer, big data architect, data scientist, data strategist, and big data specialist are some of the career options that are progressing over time.
As 2019 comes to a halt, the new breed of software developers is looking to move up the corporate ladder by shifting careers.
Here’s what these developers should start learning: –
There are various programming languages for different functions. However, as a software developer who is looking to transition into a big data career must know languages like Python, Scala, Java, C, C++, and multi-level programming languages.
A developer with expertise in these programming languages has a higher probability of getting into a data science and big data analytics job faster than a developer without these skills.
Apache Hadoop, a software library, is a framework that permits distributed processing of large volumes of data sets across clusters of computers with the help of a simple programming model. This is basically designed to upscale a single server to thousands of machines, and for each machine, it offers storage and local computation. Instead of relying on hardware for delivering high availability, a big data engineer would rather prefer the library since it has been designed to easily handle failures at the application layer. Thus, delivering high availability of service over clusters of computers could lead to failures.
It is an open-source cluster computing framework that offers a hundred times higher performance, better than MapReduce. The Spark runs in the Hadoop cluster and processes data to support a varied range of workloads. The Apache Spark components comprise of Spark Streaming, Spark SQL, GraphX, and MLlib. As software developers shift their careers in the big data domain, they need to turn to these big data technologies. Learning these technologies will not only help them earn lucrative salary compensation but will keep them around the radar of the top employers that are looking to hire.
Machine learning plays a significant role in the tech world today. Big data and ML have rather become the buzzwords for most organizations looking to scale up their businesses. In short, machine learning is a subset of Artificial Intelligence that helps computers learn and predict future happenings without human intervention.
Using machine learning, software applications can now easily augment their accuracy to predict future outcomes. In other words, software developers well-versed with artificial intelligence and machine learning concepts, will be more comfortable in using tools like Deep Code, Appvance, Testim.io among others.
We’re all using machine learning one way or the other, it’s just that we’re too busy to notice.
Quantitative analysis plays a major role in the big data world. Big data professionals need to be able to have a built-in approach using statistical and mathematical modeling techniques. This includes techniques through which professionals convert data to a numeric form. These are then further subjected to statistical analysis.
SQL databases are basically used for transactional data whose structure does not change frequently or whose data integrity is paramount.
NoSQL databases offer much more flexibility and scalability leading to rapid iteration and development. A software developer needs to have extensive knowledge in both SQL and NoSQL databases.
Other emerging skills include automated analytics, cloud data management, and real-time streaming analytics. Each of these skills are important for a software developer today, as this is the age of automation and cloud-based development.
A software developer who is more comfortable on cloud will be more in demand by the recruiters, as compared to the one who writes the code locally.
Reason… cloud allows for quicker flexibility during the process of writing codes.
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In addition, software developers should also think about learning the nuances of data visualization and data mining through online classes or certification programs available in the market.
Interesting to note is that as the requirement to organize Big Data continues to grow across various industries and sectors, there will be a surge in demand for software developers. So the developers who will give importance to continuous learning, retraining, and upskilling themselves, will always have an upper edge in the jobs market.
What are you waiting for? Now is the time to make that move…get your skills validated and your knowledge verified for an upscaling career in Big Data.