Importance Of Big Data For Software Developers |Big Data
Summary
Big Data is revolutionizing the realm of software testing and development by offering solutions to complex challenges. Software testing engineers are embracing Big Data and learning Hadoop due to its significant impact on their careers. Hadoop-related jobs are growing at 5% compared to a mere 1.6% for traditional software testing jobs. Existing testing practices face limitations when dealing with large data volumes, making Big Data tools indispensable. Transitioning to Big Data is feasible for Java experts, while non-Java professionals can utilize tools like Pig, Hive, and Sqoop. Shared skills and analytical abilities aid the smooth shift from testing to Big Data roles, enhancing software development processes and bug detection.
Table of Content
Today, software-based systems are not only pervading more industry verticals but are also becoming more difficult and complex. Fortunately, Big Data is coming to the rescue of millions of software testing engineers and developers operating globally; especially with regard to teaching them what to tell their machines to do. So, regardless of whether software developers are using yesterday’s legacy systems or grappling with the challenges of tomorrow’s hot technologies, they are finding their answers in Big Data. Yes, issues dealing with bug detection and automated knowledge transfer are being better handled with these Big Data-centric tools, analytics, and technology in place.
Why are Software Testing Engineers learning Hadoop and Big Data?
One of the most significant aspects of software domains are their testing processes. This is specifically true in case of organization choosing to adapt themselves to more improved technology. With this in view, software testing engineers and developers are furthering their knowledge in Hadoop and Big Data for furthering their career related interests (also consider checking out this perfect parcel of information for a data science degree).
Growth in Hadoop Jobs
Software testing jobs are giving way to Hadoop-related jobs and are attracting fewer returns than the latter. Currently, the optimum growth rate attributed to software testing jobs is merely 1.6% while that of Hadoop testing jobs lingers at a whopping 5%. These figures are self-explanatory and are guiding the career decisions of software developers in the existing scenario.
Limitations of Existing Testing Practices
While testing their applications, current-day engineers are being limited by their knowledge of solving Big Data problems. The standard data matching techniques at their disposal fail to work with very large volumes of data. This leads to important limitations to the skill sets of software testing engineers. Here, Big Data tools help engineers adopt unique tools that are immensely useful for testing complex datasets or trapping the opportunities in allied fields. With proper data-centric knowledge in place, they can move beyond their comfort zones and handle the testing challenges related to genomics, connectomics, meteorology, complex physics simulations, or biological/environmental research too.
Hadoop & Big Data: Easy to Shift
For Java experts, with prior knowledge open-sourced, Java-based coding frameworks, it’s a cakewalk to shift to Big Data scripts and analytics. Also, knowledge in Java is a must for Hadoop users. This does not necessarily mean that non-Java experts are in for tougher times ahead; Hadoop presents an array of tools for them too. Hadoop tools like Pig, Hive, and Sqoop rely on SQL and have little to do with Java knowledge.
Application Platforms and Shared Skills
The roles of a testing professional and Hadoop expert are not mutually exclusive. Though the idea of adopting new domains like Big Data/ Hadoop may seem overwhelming to begin with, there are many shared skills and platforms that can be aligned together for gaining results; thereby allowing software testing engineers to make a smooth transition (also consider checking out this career guide for data science jobs). For instance, sharp analytical skills, a great attitude, result-oriented technical skills, willingness to learn, and orientation to details are the common traits required for testing engineers to move to Hadoop.
How Big Data aids Software Development
In general, machines are automated for analyzing large volumes of codes and just extract the parts that software developer need to know. These bits relate to the common patterns that offer insights into how other test engineers or developers may have solved similar problems in the past. The advantage of Big Data is that it not only points out solutions, but underlying problems too. For instance, this data technology recognizes characteristic patterns that relate to bugs in the lines of codes and throws them back to the developer for timely corrections.
So, if you are a software developer or testing engineer struggling to catch on to the fast pace of Big Data deluges, then just jump on to the bandwagon and adopt the latest technologies that are trying to scare you away. With proper knowledge and advance education in place, you will be soon on top of your data related software problems, and how!
