10 Most Evolving Big Data Technological Predictions And Trends For 2022

Data has become the most valuable asset. With the rise of IoT, billions of devices are collecting vast amounts of data around the world every second and continuing digitization of businesses. Technological advancements that have the capability to collect, store, transmit, analyze and act upon the data are making it easier to gather useful information and turn it into knowledge.

This huge data inflow known as “big data” is set to become a $274 billion industry by 2022. A large part of the value is driven by the rise of Artificial Intelligence (AI), which requires huge amounts of data to train systems from predictive analytics solutions to hyper-personalized virtual assistants.

What is Big Data?

As the name implies, big data is a term that describes large amounts of hard-to-manage data – both structured and unstructured, that an organization or business inundated on a day-to-day basis.

However, it is not any type or amount of data that matters, but what the organization or a business does with the acquired data is important. The procured data can be effectively analyzed to extract actionable insights for companies and improve in making data-driven decisions in order to optimize business performance, improve existing strategies, give confidence and drive growth.

Also Read: Roadblocks On Big Data and How to Overcome Them

Why Is Big Data Important?
The importance of big data doesn’t just revolve around the amount of data a company has procured. But the value lies in the fact that how the company will utilize the gathered data. Every company has its way to deal with its collected data. Big data helps organizations or businesses harness their acquired data and use it to identify and analyze new opportunities that in turn leads to:

• Streamline resource management
• Improve operational efficiencies
• Optimize product development
• Drive new revenue
• Growth opportunities
• Enable smart decision making

Big data technology is being adopted by most prominent sectors like healthcare, banking and security, insurance, and even government. So, how is big data and analytics evolving with the new technological innovations like artificial intelligence, machine learning, IoT, and blockchain? Here are some of the most exciting predictions and trends for big data analytics to look forward to in the coming years.

Augmented Analytics
Managing structured and unstructured data is a time-consuming task and takes up as high as 80% of data scientists’ valuable time. Augmented analytics is proclaimed as the future of business intelligence that engages statistical and linguistic technologies to improve data management processes. Augmented analytics is aimed to resolve by automating the time-consuming task of data processing to create an analytics-ready data pipeline. The augmented analytics market is expected to hit $18.4 billion by 2023.

Cold Storage And Cloud Service Optimization
Data never goes out of fashion. Organizations and businesses need to understand what to do with the data, which is trapped in data silos and legacy systems. Optimizing cloud services for viable data solutions is changing the way for enterprises to store and deliver data on the edge. As the amount of data generated reaches the mark of more than quintillion bytes, cold storage solutions could save half of the overall data storage costs.

Continuous Intelligence
Continuous Intelligence (CI) is an integrated data pipeline that will automate decision analysis. This technology makes it possible for big data insights accessible to the business along with the decision-making process and influences automation efforts. The emerging technology – continuous intelligence aims to deliver custom intelligent solutions that surround big data to match the customer’s needs and expectations. The trend of Continuous Intelligence is expected to gain momentum by the end of 2022 and half of new businesses will deploy CI in the upcoming years.

Blockchain
Several ongoing debates are surrounding big data – its veracity and data privacy. But, blockchain can assure big data security along with making it accessible only to its stakeholders. Through upcoming technological trends, it will be interesting to look for how AI and ML models are devised to operate on the top of distributed, immutable, and transparent blockchain-generated data.

Dark Data
Every second, we generate mammoth quantities of data from our digital foot and enterprises end up using only a fraction of it. The remaining data gets trapped in dark data silos. Dark data is nothing but a huge chunk of unstructured data. It considerably holds potential information on customer behavior, target markets, and competitors analysis.

Edge Computing
The COVID-19 pandemic led to a new era for businesses to move their operations into the cloud. Subsequently, the Internet of Things (IoT) devices rose over the internet. That need for IoT devices has bought a trend of cloud computing and edge computing. These emerging technologies utilize the most critical data, process and store data in a location that is readily accessible to the IoT devices, ahead of transferring to the cloud for further processing.

Big Data-as-a-Service
Big Data as a service (BDaaS) brings together infrastructure, data warehouse, platform service models under a unified platform to deliver enhanced big data analysis efficiently for intelligent business insights. BDaaS helps businesses to enjoy multiple benefits of data ETL to deliver through Data Warehouse and Data Lake as a Service. It is predicted that BDaas will drive the future of global economies. Its ability to drive into omnipresent data resources securely without saturating in building a data community.

Real-Time Analysis
Real-time big data analytics from data pipelines will generate intelligent actionable insights for businesses. This eventually helps in detecting cybersecurity threats and also evaluates the performance of critical infrastructure, applications, and services deployed over the cloud. Real-time big data analytics will find its way to being a promising trend for many businesses in the coming years.

Self-Service Business Intelligence
Self-service business intelligence (BI) will seamlessly drive the movement of big data across data warehouses over the entire value chain. Self-service BI helps businesses integrate data-driven frameworks through enterprise resource planning, marketing automation, Customer relationship management, and financial programming. This emerging technology would give more privilege for developers to build more personalized experiences for their customers, enriching big data-driven actions utilizing the business intelligence loop.

Big Data Strategies
Big data strategies would be driving their success across multiple sectors such as transportation, telecommunications, insurance, automotive, retail and e-commerce, and much more. The advancements in Natural Language Process (NLP) technology will help big data stakeholders to engage their customers over personalized data conversations. The big data strategies ability to operate undifferentiated data will provide an in-depth understanding of the digital transformation by cutting edge analytics.

The Wrap
Big data is a trending technology and is being increasingly encouraged by startups to large organizations to improve customer experience, achieve better-targeted marketing, and reduce costs. Further, many companies are showing interest in big data analytics for its ability to improve data security. So, now you got an insight into exciting big data analytics predictions and trends for 2022 that will take the technology world by storm.