Big data is still a relatively new field in data science. It has made a significant impact in the analytics world, and big data technology and platforms will continue to change as technology evolves. That's why it's so important to understand upcoming trends in big data that we'll be seeing in coming years.
Over the last few years there has been a lot of discussion about Hadoop and big data technologies, and the IT industry has been debating considerably on their future. The main concern has been whether Hadoop and big data will be considered part of mainstream technology or whether it will be considered a niche area. As we have seen in the past, there have been many innovations in technology that weren't ever used in mainstream industry, but rather were used in silos for special computing purposes.
In a very short span of time, big data has come to be a mainstream technology. In 2013 and 2014, we saw enterprises taking initiatives to move big data applications into production. In earlier years it was only a type of POC (proof of concept), where companies were validating the technology and its output. Now in 2015 and in the coming years, there will be a lot of implementation of new use cases. Most of these use cases will be based on real-time analytics and obtaining more actionable insights.
In the coming years we will see a huge impact from big data in almost every industry. Data is at the core of every business, so it must be tapped and analyzed properly. Big data and its related technologies will enable us to capture, process and analyze data to get meaningful insight. The big data trend will continue to grow and empower us to understand its value as we never have before.
Now, let's take a look at some of the important big data trends we'll see in the coming years.
Natural Progression of Hadoop Vendors
Hadoop is a basic technology platform for big data processing. However, the basic Hadoop platform does not provide all the flexibilities and advantages needed to properly process all the data, so handling big data processing on this basic Hadoop platform can be tedious and complex.
There are now a number of Hadoop-related technologies like Hive, Pig and many more, which are known as the "Hadoop ecosystem." These technologies are based on the Hadoop platform and make handling big data more manageable. There are different vendors like Cloudera, MapR, Hortonworks and also IBM, which provide Hadoop technology stacks. These technology platforms are built on the basic Hadoop framework, but are more user friendly and compact in nature. They also provide proper user interfaces to work on different processing tasks. As a consequence, companies can focus more on business logic rather than on platforms.
The growth of these Hadoop vendors will continue in the coming years, and their offerings will have a lot of impact. The Hadoop vendors will position themselves as solution providers and help the organizations to implement their big data applications.
Big Data and Cloud Integration
In today's world, cloud computing and its related infrastructure is inevitable. On the other hand, big data applications are growing rapidly. Organizations are implementing more and bigger data applications to get more insight from the valuable data. As we know, big data applications deal with huge volumes of data, and these data are processed in a clustered environment. Distributed computing is at the core of all big data processing applications. Therefore, the distributed computing infrastructure should be maintained properly to overcome failure, errors or any other fatal issues. The cloud environment is the most suitable to cover all these issues. Big data applications can run on this cloud infrastructure (consisting of a clustered environment) and provide efficient and continuous output. Organizations do not need their own infrastructure and IT team; instead they can rely on cloud infrastructure, which is also cost effective. Therefore, cloud integration with big data is going to be a powerful force.
Big Data and Security Issues
Security issues are a big concern for all big data applications. As we know, data is the key to all big data applications, so we need to understand the security threats well in advance. Organizations are working on big data applications to analyze structured, semi-structured and unstructured data, which will give them meaningful insight and business direction. This valuable data and its output is the key to all business decisions, and hence must be kept confidential within the organization. Unfortunately, not all big data applications are designed with security issues in mind. As a result, these big data applications will face security threats. Therefore, implementing security solutions for big data applications will be a major task in coming years.
Offering Big Data as a Service
We're all familiar with the SaaS model, where applications run in a cloud environment and users access it as a service. The payment model is also flexible, where users only pay for what they use. The same concept is going to be applied to big data applications as well. Different big data product companies are already hosting their applications in the cloud and offering it as a service, and users are accessing it as a service and paying on a usage basis. In the coming years, more data companies will be offering big data as a service.
Big Data and the Internet of Things (IoT)
The Internet of Things (IoT) is the latest buzzword in the tech industry. IoT basically consists of different devices fitted with sensors for capturing data. Now collecting all this data and extracting meaningful output is the biggest challenge. These devices are used everywhere — homes, industries and even wearable tech — and they are capturing a significant amount of data. This sensor data is also a type of big data, so using and processing it in a big data platform is going to be a big challenge for organizations.
Big data seems to be here to stay, and the ways we deal with it will continue to change and grow. Apart from these five trends, there will be many more challenges and emerging trends in the coming years. Cloud and IoT will be ever-present along with big data applications, and these technologies combined will be a powerful tool for data analytics.