Java has been in use for over 20 years, which makes it ancient in the digital world. Big data, however, is much younger and is still relatively new in the world of IT. Although the concept of ‘big data’ has existed for a while, the actual usage (on a large scale) is much more recent. Per its definition, big data is large amounts of structured and unstructured data, which through analysis can lead to new insights and better decisions. In this blog, we’ll explain why Java is an important skill when it comes to Big Data and the Internet of Things!
Although we have the tools for big data analysis, this doesn’t mean we can analyze all of it. According to professor Patrick Wolfe of UCL’s Big Data Institute, we produce too much data too fast to analyze all of it. The idea is to turn data into meaningful insights by developing the tools or techniques that could make predictive analytics easier and faster.
This is, however, not where it ends: Antonio Regalado goes even further and claims that only 0.5% of data created is analyzed. As a result, developers are hard at work to improve computation capacity and increase the amounts of data that can be analyzed.
As data volumes continue to increase, the need for data analysis has grown rapidly. There are multiple possibilities when it comes to data analysis, and one of them is Hadoop. Hadoop is a Java-based programming framework offering high-level computational power able to process large data sets. Professionals with Hadoop skills are in high demands due to the increased demand for big data skills. Academy Cube offers various courses that teach you the ins and outs of Hadoop!
What is the role of Java in all this? As Java supports predictive analysis, it’s an important instrument in the collection and analysis of big data.
If you want to understand the role of Java in Big Data and Internet of Things, think of Internet of Things as the senses, Big Data as the fuel and artificial intelligence as the brain that predicts future outcomes. With the growth of the Internet of Things, millions of people and devices gathering data online, this leads to the need for Big Data technologies to store, mine, and extract these immense amounts of data in the best conceivable way.
Java has the power to analyze these large amounts of data collected by IoT sensors. Moreover, Google and Apache contribute their codes and information, and the internet of things become accessible with available code and data.
Because of these overflowing data streams, the use of artificial intelligence has become essential if you want to gain any insight from big data analysis. With the help of the Internet of Things, big data has become more valuable than ever in nearly all industries, for instance by fostering real-time decision making such as analyzing agricultural crop patterns, tracking suspicious activity at ATMs or predicting the behavior of a smart car driver.
In 2018, the collection of data is no longer limited to personal devices such as smartphones or laptops. Big data has become even bigger due to the large numbers of new IoT sensors introduced into everyday life. Cars have become smart cars, and cities have become smart cities – both collecting massive amounts of data.
Businesses keep on investing in big data and IoT technologies. This means that it is expected that demand for data scientists and IoT experts keeps on rising, and a career in these fields is a future-proof choice. If you want to dive into the interesting world of big data, you need to know where it comes from and how it is processed.Topics: Digitalization, Big Data, Internet of Things, java