2021 is here. A new year and a new beginning. Data is expanding at an exponential rate and new technologies and trends arise to make the best use of data and save time. Here is an article on the top 4 Big Data trends for this year that everyone should know.
1) Actionable Big Data
Big data constitutes data from all possible sources. However, not harnessing the value of data faster results in lowered data value. 2021 would see the trend of actionable big data, where the big data can be made usable faster. Being able to utilize data as soon as possible makes it much more valuable. Thanks to the improvements in data integration, analytical modeling, and data governance, enterprises can gain from the actionable big data. Some of the methods to make data much more useful include real-time data processing, IoT, in-memory computing, and edge computing.
2) Cloud Automation
The cloud operates on an on-demand basis, yet still there are some important tasks. For example: 1) Holding the data, 2) Tagging the data, 3) Governing the data, and 4) Utilizing the data. It takes lots of manual effort to manage the resources, test them, and scale them accordingly. This is where cloud automation helps the organization.
Technical teams apply cloud automation to create, modify and manage cloud resources automatically. Cloud automation reduces the burden on the cloud, so that complex tasks are executed easily. AI, AIOps and machine learning are applied to review the data, discover the trends, and analyze the results. Furthermore, cloud automation combined with capacity planning helps to cut down operational costs, by combining resources or even shutting down unneeded resources.
3) Modern Data Exchanges
Online marketplaces are one form of data exchanges, where everyone buys data and sells data. This form of modern data exchanges act as the platform to integrate third-party data offerings. Consequently, this service is predicted to accelerate developments in cloud, AI, and machine learning. For example, SingularityNET is a decentralized AI network which offers developers and enterprises to create, share, buy, and sell AI services or models.
Hyperautomation is the combination of technologies such as Robotic Process Automation (RPA), AI/ML, NLP, Bots, and Process Mining. It is used to automate business processes in the field of big data. Furthermore, the automation helps enterprises to visualize their business processes and gain real-time intelligence.
Hyperautomation facilitates automation of complex dependent tasks. Besides, it provides a quick way to engage the players in business digital transformation. Hyperautomation paves the way to a digital workforce, that can do the repetitive tasks and boost employee performance. In addition, the digital workers connect to different business applications, work on structured and unstructured data, analyze data, and discover processes and new automation opportunities.