It’s no news that big data analytics are changing the landscape of how businesses are managed. Thanks to the new improvements in the cloud and the additional technologies, the reach and usage of big data are far-reaching. Many of our interactions with businesses are online and with the huge volumes of data we leave behind every time, it’s becoming a gold mine for brands. The introduction of Artificial Intelligence, Machine Learning, IoT and other latest technologies has upped the quality of data-oriented solutions.
Big data plays a pivotal role in shaping various industries by deciding how brands interact with information and create better products for customers. As the scope of big data is expanding, there are a lot more applications of big data analytics than it was previously. As we head to the next year, let’s see some of the new trends of big data for the year 2021.
The Big Data Trends of the Coming Year 2021
Augmented Analysis
Augmented analytics is one of the emerging trends that banks heavily on big data. In research published by Gartner in the year 2017, augmented analysis was said to be ‘the future of data and analytics.
Through the process of augmented analysis, the process of data analysis is automated by using Machine Learning and Natural Language Processing (NLP). This analysis enables in providing clear results and presents the solutions in a simple and easy-to-understand format. The data in this process is prepared through a streamlined automation process from various sources like external portals, internal data, cloud data and any other locations.
The analysts can combine all of this data, process them, check them for redundancies and errors and prepare them for analysis. These clarified data can also be stored in the form of clusters or used for quick real-time analysis with sophisticated tools. Then the data analysis is automated with algorithms to identify the trends and patterns and provide accurate results.
The augmented analysis will be hugely beneficial for businesses:
- To collect and format the data from different sources.
- To manage tons of data at the same time.
- To improve the day-to-day functions in a business.
- To quickly prepare and analyze data on time-sensitive requirements.
- To allow the analysts to make time to work on special projects.
Leading the Digital Transformation
There would be no digital transformation without data. Most of the new technologies developed to help business operations require the help of big data. In the year 2021, it is expected that more companies will embrace the digital and convert their business operations from manual to online.
Once a business goes online, it is bound to leave a trail of data and collect outstanding data from its customers on websites, social media and any other forum. Soon enough, with the digital transformation becoming a priority for many businesses for the year 2021, the world of online is up for a never-seen-before evolution.
According to a survey by IBM, 1 in 3 business leaders don’t trust the information they use to make decisions. Also, with over 30% of companies’ customer data inaccurate, there is a growing need for digital transformation, which helps companies effectively rely on data without doubting its authenticity. New AI and machine learning tools, when combined with big data, will guide us to understand the data we generate every second without any false positives.
Data-Backed Tools
The Internet of Things (IoT) is growing, according to Gartner, and is expected to reach 8.4 billion by the year 2021. These IoT devices are already used in some places for parking meters, refrigerators, ovens and several other home appliances. Further, in the year 2021, IoT devices are expected to play a major role in security apparatus, healthcare equipment, smart home devices and retail devices.
The IoT devices will be at the forefront of physical devices that leverage the benefits of data and also assist in running big data analytics. For example, edge computing is a new method that allows the data to be stored in the local storage device near the IoT device instead of in the cloud to manage data better. As it reduces the dependency on the cloud platform, it helps the applications to work faster without any wait time for accessing the data from the cloud.
There are many such new improvements of data-backed tools that help in data management and analysis, and also for consumer products that are stated to improve in 2021.
Data-As-A-Service
Data-As-A-Service is not new but still is one of the underplayed uses of big data. Typically, Data-As-A-Service means accessing the data online from shared spaces. It is useful for employees in large organizations who want to share huge volumes of data between departments but are unable to do so due to technological limitations.
Data-As-A-Service is similar to downloading music and movies from the internet. This Data-As-A-Service architecture will be a central hub in organizations that promotes self-service and improves the productivity of the organization. Also, the data is kept in one place, so it is easy to maintain.
Evolution of Healthcare Services
Big data is helping in healthcare services for various purposes. Researchers believe that the mass volume of medical data available can help to identify the cure, preventive measures and other disease management solutions. Though there is no proper central body that connects all of these medical records as of now, there are some progressive steps stated for 2021 which is expected to make a difference.
The IoT devices are also playing an important role in managing hospital equipment. The year 2021 will be a stepping stone to see a major revolution in the healthcare system backed by big data analytics. Some researches are underway about discovering the use of IoT devices in patient tracking and monitoring of patient conditions. Some scientists are also creating robots using big data to be present in patients and perform operations.
R&D in Various Industries
Big data analytics is improving the way businesses manage their everyday operations from marketing to supply chain management. The organizations can gather behavioral insights, customer preferences, forecast industry trends, customer expectations and create better products that customers wish.
The R&D department in many industries require the help of big data analytics in various aspects – simple social media management and analytics, manufacturing automation, improving product quality, providing better customer support, location-based service decisions, sophisticated tools to automate sales pipeline and a lot more.
The powerful algorithms of big data analytics services can be put to use intelligently to improve the business reach and increase business productivity.
On a Final Note…The futuristic needs of big data are enormous and the year 2021 will mark the release of new applications of big data as well as witness the introduction of new research to include big data to develop automated physical products. As a business owner, it is vital to invest in big data analytics and explore its applications in your industry and take the lead in product innovations.
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