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Emerging trends in big data technology 2021

2020 didn’t appear out to be so well for businesses and created consequences in many other fields. IT departments are the ones who suffered in endless ways, but the pandemic didn’t hold them back; they stood up boldly and faced it. It was a massive change to shut down all the offices and opt for work from home and do online conferences where cloud computing played an extended corporate role.

For the past few years, big data technology, which was meant to be so mysterious, has begun to eventuate in 2020. Working from home has not been a big deal, and human beings have proved no matter that you work from home or in the office, staying productive is the only solution. To experience Cloud automation, hyper-automation, etc., these are the pragmatic intelligence that comes into an action to alter the technology perspective in 2021 entirely.

Practicable data:

According to the study, the year 2021 might be the first year in overall decades to experience that big data and artificial intelligence have the potential and can be put into action. The data gets faded with the decades, “Practicable data” makes it easier to store valuable business intelligence and data integration information.

It brings a satisfactory change via digital channels, edge computing, the IoT, in-memory computing, which enables connecting with the customers instantly with the combination to make data and information not just more practicable but much more perceptive and useful. Overall, data integration, data governance, and data visualization improvements make data more convenient and, therefore, much more practicable.

Hybrid Cloud:

For the past many years, many industries don’t find it comfortable and valid to share their data information on the Cloud because of the poor latency, security, and privacy issues. To combat these multitudes of reasons, this is where Hybrid Cloud comes to the rescue. Hybrid Cloud has a software feature that enables the communication function between each different service. It is a solution that merges a private cloud with more than one public cloud service. Utilizing Hybrid Cloud in the business strategy helps to move the workload more flexibly among cloud solutions as per cost fluctuation and needs.

The Hybrid Cloud links at least one private Cloud with a minimum of one public Cloud. Private Cloud is an internal network, and it is limited to a select group of users. Whereas, in the public Cloud, the service can purchase over the public Internet by an unlimited number of users. The service offered by third-party vendors includes Google, Amazon, Microsoft, etc.

Utilizing Hybrid Cloud helps the company’s workload maintain data under a single cloud infrastructure by linking one or more private clouds to public clouds. Overall, it creates a more expansion network by improving developer productivity, Strengthening a company’s privacy and security, enhancing greater infrastructure efficiency, and regulating compliance systems. Also, it speeds up the innovation process and accelerates a product’s time-to-market.

Data exchanges and market places:

According to global research, Gartner predicts that online marketplaces will induce 35% of large industries to become sellers or buyers of data by 2022. These big data trends should promote data science, AI, Cloud, and machine learning declared Gartner. ZoomInfo, Acxiom, and White Pages organization have been selling data for many years now. But these new data exchanges offer places to combine third-party data providings.

Cloud automation:

Detaining big data can be easy to perform but confining it, labelling it, and governing it, using it requires many behind-the-scenes resources. Cloud computing comprises services when needed, but if you view it practically, someone needs to “accelerate those resources.” Observe them, check when they are no longer required, and erase them down for all these activities; a manual effort is needed.

Cloud Automation assists IT developers and teams alter, create, and automatically take down the unneeded resources on the Cloud. Cloud Automation eases the work of cloud systems, both private and public, and performs complicated tasks with a single tap of a button.


  • To review large volumes of information and logs and analyze results, AI, AIOps, and machine learning help to do it.
  • Utilizing Cloud Automation is cost-efficient because it takes down the unwanted resources and helps to solve issues suggestively even before they occur.

Hyper automation:

Using Hyper automation would run for a longer term even after closing the chapter in the year 2021. Because it’s a combination of machine learning software, the automation tools are required for the automation process, including the discovery, monitoring, analysis, measurement, reassessment, design, and assessment work of the technology.

In simple words, Hyper automation helps the organization to view their process and operations by creating digital twins that effectively recreate an organization’s system process, which offers instantaneous intelligence about the business. It also deals with implementing cloud big data technologies and advanced technologies to automate business processes and elevate humans.

Captivating experiences:

There is no time long where everything on the smartphone will soon be possible on extended reality XR with new fascinating experiences. In addition to that, a range of new apps will be produced that are only possible using virtual reality or augmented reality. In today’s latest technology surrounding virtual, augmented reality technologies have become more alluring and engaging than the past versions. When interactive business applications and 3D films opt for using XR, the prices for VR will drop down surely. Today’s VR headsets allow users to explore and interact with virtual objects in VR 3D worlds.

Collaboration of XR with VR says that virtual reality has fully artificial environments. Augmented reality permits virtual objects to be presented in the real world; lastly, an MR is one step forward, offering users the ability to manipulate and interact with both virtual and physical items. With the help of imaging and sensing technologies.

Cloud to the edge:

The utilization of the Cloud to edge solutions includes data collection and ensures security, deep data analysis, regulatory compliance, and privacy. Because edge computing carries out storage and transmission capacity close to wherever the information data is collected, analytics performed at the edge can be much more perceptive to things happening in the real world.

When data is processed using the edge of the Cloud, it will save lots of time, effortless and cost-efficient. Analytics modelling makes them more convenient and useful by producing the results quickly and sharing huge amounts of information over a private or public cloud network. 

There must be building models on those systems to attain the results, then moving the results down to the edge devices; therefore, it involves a long process. Sometimes, the acquired results of models may go in vain because the data information has gone uninterested and dry. It is better to use the edge to process and capture the data, then disperse it to necessary parties as required and quickly as possible.


Practicable data is operating through hybrid clouds, data marketplaces that assure affordable AI models, a perfect tool to keep the company’s information secure, captivating technologies that turn virtual meetings into VR playgrounds. And hyper-automation assists in keeping everything running effectively to make the year 2021 incredibly interesting via big data analytics technologies.