What’s Big for Big Data for 2022?
As if big data wasn’t big enough, it’s going to get even bigger in 2022! At least, that’s what the industry pundits are predicting through their crystal globes.
Statistics indicate that new information generated per second per human being will be around 1.7 megabytes by 2022. Data scavengers have a huge onus lying on their shoulders to sift through the massive data to present it in structured and meaningful information for businesses. It wouldn’t be surprising to watch corporate and educational institutions launching
big data analytics program to meet the industry demand and cope with the changing business dynamics.
Let’s take a look at what big things lie in store for big data 2022 year.
Enhanced Sophistication in Enterprise Data Architecture
As the data world become more voluminous and complex, it is getting increasingly difficult for organizations to operate on physical servers. Hence, they are moving to cloud-based data architecture. 2022 will witness enterprise data architecture going several notches above in terms of advancement. Organisations will prefer data frameworks which allow scaling as per the business needs, real-time analysis of real-time data and integrated deployment across cloud and mobile devices.
Also Read: Kickstart your Career in Analytics with Data Science Program
The data warehouse providers such as Amazon Redshift, Big Query and Snowflake and BigQuery have established their roots firmly in the market and will now begin a fierce war to grab the largest pie of the market share. At the same time, the demand for new data warehouse providers will increase. It might also be possible that an organization start exploring data lakes model to reduce costs.
Prescriptive Analytics to Gain Momentum
If 2018 was ruled by predictive analytics, it now turns of prescriptive analytics to show its power! Leveraged to answer the question ‘what should be done’ and arrive at solid recommendations based on historical insights, prescriptive analytics will become the most adopted model of analytics in organizations, especially in the healthcare and retail sector.
Robust Growth of Internet of Things (IoT)
Did you know that currently there are more than 20 billion connected devices across the world? (Source: Ihsmarkit) 2022 is touted as one of the most exciting phases in the development of IoT. As people continue to own more devices and expect them to perform smartly and stay digitally connected, IoT will climb several rungs in the big data ladder. IoT has a tremendous scope of retail, healthcare and financial sectors which are leveraging artificial intelligence, machine learning and more recent trend blockchain technology in a big way. This year, organizations will look at the interoperability of IoT with other technologies for efficiency and optimization.
Also Read: How is Big Data Analytics Different from Data Science?
Emergence of Dark Data
Dark data is nothing but a subset of data. It pertains to data which is lying passive, unused and unanalyzed in data repositories. However, 2022 will change how data miners and decision-makers perceive dark data. According to the Deloitte report titled ‘Dark Analytics: Illuminating Opportunities Hidden Within Unstructured Data’, the industry is all set to experiment with dark data and analytics to unearth information for highly personalized and nuanced business offerings. Deep web technologies will come into the limelight to tap into the secrets of the dark data world.
Faster, Accurate and Unsupervised Machine Learning
There has been a big bang alike explosion in the field of
machine learning. With improved algorithms and availability of ultra-modern, powerful hardware, machines learning in the form of robots and self-driving cars have set an unparallel pace for future. As the learning curve improves, machines will perform their tasks faster and more accurate than what was expected from them. However, the biggest story on machine learning to unveil in 2018 would be that machines will need minimal human intervention to function.
Sophia, the humanoid robot and Google’s Deep Mind AI are fine examples of unsupervised machine learning. Remember the media sensations that Sophia created by being granted citizenship of Saudi Arabia? Even creepier was the video footage of Deep Mind AI walking, jumping and climbing by overcoming obstacles that it was never programmed to perform!
As machines begin to teach themselves, it will help human minds to penetrate into rigid and complex data that they never ventured into before.
Cognitive Technology to Take Centre Stage
Experts say that cognitive technology could steal the limelight from artificial intelligence. Like IBM’s Watson, machines would be able to understand, reason, interact and learn in a similar way humans do. Through its higher emotional sensibilities, cognitive technology machines will transform the way businesses are done. Instead of pre-programmed settings, they will absorb the happenings through their experiences. Going forward, machines will not only handle data but also present it in a way that it becomes less daunting for humans to interpret data.
Cyber Security Measures to Increase
In the wake of cyber attacks like WannaCry and Petya that shook the organizations and governments across the world, there has been an increasing shift towards robust cybersecurity measures. Organizations would want cybersecurity solutions that are preventive, not reactive.
If you don’t want to miss these trends, it’s time to learn more about them through big
data analytics courses.
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