It has already been a few years since hyperautomation started being talked about as an important technological trend, and it’s now considered as a growth factor for companies. Some people still think that this process is a threat to their employment, but we’re going to see today that hyperautomation optimizes people’s work and doesn’t replace them.
What is hyperautomation?
Simply put, hyperautomation is a process which automates every process that can be, using advanced technologies like AI and machine learning.
What are the benefits of hyperautomation?
TechRepublic explains that the hyperautomation of processes allows for the centralization and synchronization of interfaces, thus improving productivity with better access to data. It also eases the integration of new processes.
Regarding the hyperautomation of the data pipeline, it takes care of low-value tasks, speeds up the access to data for all users, makes the integration of new data easier and breaks data silos, among other things (see image below).
This easy access to data and automation of low-value tasks frees up the data scientists and analysts, who can then work on high-value tasks, thus adding to the company’s value in the long run.
Right now, hyperautomation is implemented at the top of big companies, but data democratization and the arrival of new and cheaper platforms are contributing to the popularization of this practice.
How can we put hyperautomation in place?
Before doing anything else, the company must ensure that all its files and data sources are digitalized.
After that, according to RTInsights, a company can automate simple tasks to determine and optimize the hyperautomation process according to its needs.
The hyperautomation of processes includes the integration of apps and systems used in the creation and management of the company’s data. That means implementing an iPaaS and an APIM (Application Programming Interface Management), as well as a low-code development tool used to create mobile and web apps using APIs and integrations.
The hyperautomation of the data pipeline exploits AI, machine learning and APIs for each step of the pipeline, from the collection of data to its analysis (see image below).
This process of hyperautomation improves operational efficiency and lowers the chances of errors, since it automates each step of the pipeline and automatically updates data.
To go further on hyperautomation, take a look at our white paper, The data-driven enterprise, season 2 episode 1: the one that hyperautomates, and our webinar, Hyperautomation – Make your data pipeline smarter, on the subject !