Introduction

In the last five years, the landscape of big data analytics has witnessed an upheaval. The embracing of big data by startups and a sudden interest of technological giants for analytics is testimony to the fact that data has dominated the first two decades of the twenty-first century. To talk about statistics, the net worth of the big data industry as we speak is about 200 billion dollars. If this industry continues to grow at this pace, it would reach a net worth of 270 billion dollars by 2025.

In one word, big data is the most prominent subject of research in the coming times. This article aims to understand both past and future prospects of big data.

Reflections from the past

The gradual rise of big data analytics

It needs to be mentioned in the beginning that there was a considerable gap between the arrival and optimization of big data analytics. This is because the maintenance of large scale data operations proved to be a costly affair. In order to operationalize big data in real sense, we needed to conceive a framework. As this framework started to build up, the domain of big data attracted a large number of followers. The billion dollar startups which we now call as unicorns were first to visualize the worth of big data. As these unicorns started harnessing the power of big data, they witnessed a rapid surge in their profits. Others were quick to follow this trend and gain insights into data. They laid special emphasis on big data analytics training. The snowball effect led to big data analytics enlarging its sphere of influence in the business world.

The amalgam of analytics and AI

In the past, artificial intelligence and machine learning have played a great role in contributing to the science of data analytics. The three features of artificial intelligence, machine learning and big data analytics have formed a triad which has become ubiquitous in the present times.

It needs to be mentioned at this point of time that traditional data analytics was quite different from the present domain of data science. While we had a dedicated data engineering team dealing with big data analytics in an organization in the past, we now see a constant overlap. Big data analytics is slowly invading all the important spheres of a company and it can no longer be dealt in isolation.

Predictions for the future

The new world on the cloud

As the world on the cloud continues to expand, businesses look for their sweet spot on it and this is where the question of data migration comes into play. However, even after opting for data migration, the threats of cyberattacks loom large along with the pointer of privacy. Moreover, the process of data migration may prove to be challenging as companies would need weeks or even months for complete transfer of their prevailing platforms to the cloud. The solution lies in hybrid deployment in which the robust and dynamic data can be switched over to the cloud and other essentialities can be operated as such.

Hence, the future trend would be the adoption of hybrid cloud solutions to manage the upcoming streams of big data analytics.

Databricks and Spark vis a vis Hadoop

The enhanced processing capacity, interactive interface and effective task sequencing of Databricks and Spark has challenged the monopoly of Hadoop. Moreover, the testing of Databricks in a sandbox gives outputs which prompts its adoption. That said, the future trend may be the coming of new products which would usher in rapid competition in the business market.

Digital transformation is on cards

The idea of digital transformation created a great hype in the last few years. But the reality is that the real digital transformation is yet to happen. By definition, digital transformation is the adoption of digital technologies into all spheres of a business ecosystem. It is said that the real digital transformation would induce a necessary disruption in all strategic areas of a business. The drivers of digital transformation would be big data analytics training, cloud solutions, artificial intelligence, internet of things, blockchain technologies, machine learning, computer vision, deep learning, advanced algorithms, intelligent systems, sustainable solutions and decision intelligence.

Concluding remarks

Big data analytics has induced a timely evolution in various sectors and the time is not far when we will begin to witness digital transformation taking place at it’s best.