Big data is no longer a buzzword; it seems to have comfortably crossed the threshold of early adopters. The following post emphasizes on how big data can morph the shape of business in the upcoming years.
The need to manage quintillions of bytes of data every day has compelled businesses to focus towards data-driven decision making. Due to which data gathering, data analysis, and data implementation have become a crucial part of mainstream practices. Earlier the concept of Big Data was primarily deployed by large businesses especially those who could afford the tech whereas, in the present scenario, even small to medium-sized enterprises have started relying on the same for intelligent business insights.
Big data services have indeed come as a boon, but they even have a fair share of controversies as well. I completely understand the value of is the never-ending stream of information, but at the same time, it becomes quite challenging to draw actionable insights from such vast pool of data, either structured or unstructured. Fortunately, we have artificial intelligence, cloud computing, internet of things to the rescue. With the help of these techs, even the complexity of the big data can be handled smoothly to one’s advantage. That’s why we say it is not just the latest fad; it is a gold mine that very few have realized its true value.
With the dawn of 2019, new concepts & technologies regarding big data will grow popular like never before resulting in fading the old ones. The best is yet to come, and hence the future is going to be exciting for all of us. Let’s keep the fingers crossed! Let’s dive right in, shall we?
Streaming the IoT for Machine Learning
Several efforts are made when it comes to combining streaming analytics and machine learning. In 2019, one can expect significant research and implementation regarding the same. If we look at the current machine learning scenario, it uses “stored” data for training, in a “controlled” learning environment. By implementation of the new model, useful information can be provided to Machine Learning in real time by streaming data via the Internet of Things. All this happens in a less controlled environment. The primary goal is to provide more flexibility and appropriate responses irrespective of the situation. Moreover, it has a special focus on communicating with humans.
Of course, this requires a more complex algorithm. With the ever-growing evolution of the primary models, systems will automatically coordinate to match the changes, as needed.
Emergence of Augmented analytics
According to Gartner, it is the third wave for data and analytics capabilities. It is found that day in day out companies are shifting massive amounts of data through automated algorithms. And by the year 2020, 40% of the data analyst task will be automated. This will also increase in number; i.e., five times faster than professional data scientists during the same period.
Politics and GDPR
2018 was all about the European Union’s General Data Protection Regulation (GDPR) but have you wondered what the future holds. Although GDPR is focused in Europe, organizations are endeavoring hard to simplify their business and promote good customer relations. In addition to this, they will provide some privacy protections for all their customers, irrespective of where they reside. Due to which many businesses across the globe have chosen to revamp their existing consent procedures and data handling processes. Today, if you wish to conduct business with Europeans, all you have to do is to come up with new procedures for notices and receiving consent. However, I have come across many of you who are currently trying to plan for what’s next, while others are seen simultaneously struggling with problems in the present.
In 2019, the U.S. government will be seen making an effort to imitate the GDPR and hold businesses accountable for the way they handle privacy and personal data. Let’s see what’s in there for us in the upcoming years.
The popularity of Hybrid Clouds will increase
In the year 2019, the prevalence of hybrid clouds is more likely to increase. Typically speaking, any application or data in a hybrid cloud can be transferred in on-premises (private) clouds and IaaS (public) clouds back and forth. This gives rise to more flexibility, deployment options, and tools. It may also interest you to know that a public cloud can be used for the high-volume, low-security projects, such as email advertisements, whereas the on-premises Cloud can be used for more sensitive projects, such as financial reports.
As the big data technology matures, several enterprises have started accessing significant rewards. For example, the use of AI platforms to process big data results in gathering Business Intelligence and improving efficiency. As a result, automating basic tasks, preventing the duplication of efforts, and eliminating copying, data processing, and constructing ideal customer profiles- simple yet time consuming activities becomes easy.
Advancement will continue to leap across several industries to create a better society through smarter procedures. In order to receive benefits through such trends, it is imperative to understand how they are used effectively and how they can help you in making the business grow. I must say that this is only the beginning of what’s possible.
Kibo Hutchinson is a Technology analyst at TatvaSoft UK which is a Java & Big Data Development Company in London. She strongly believes that knowledge is meant to be shared and in this post she is sharing her insights on Big Data.