Robotic process automation (RPA) companies are trying to deliver a "fully automated enterprise," but even that promise may be too optimistic. Current trends indicate that RPA has much more potential, especially when combined with data science. If you have already worked with both the technologies of Data Science and RPA, your views are most welcome in the comment.

Robotic Process Automation tools started with computers doing repetitive tasks that humans do. The label "robot" is essential here. It's a metaphor that software is not contained in systems but is connected to all (or many) information systems that human workers touch.

RPA developer and data scientist skills: Different But Harmonizing

When leaders bring RPA developers and data scientists together, the benefits to the organization are greater than the sum of its parts. By partnering with data scientists, RPA developers can automate far more complex processes than they could be alone. Data scientists working with RPA developers can work faster and stay focused.

Both RPA developers and Data Scientists prefer Python over other programming languages. The knowledge gap is smaller. There is also a desire to fill this gap. Our findings show that RPA developers are already interested in learning more about data science-related topics. In the 2020 UiPath State of RPA Developers Report, several of his RPA developers say they want to extend capabilities beyond RPA to include ML and data science. Even data scientists are not immune to gaps. Data scientists working with RPA developers can work faster and stay focused. Although there are few differences, RPA developers and data scientists speak, or at least program, the same language.

Researchers noticed that RPA developers can do those tasks quicker on which data scientists spend nearly half of their time. Recall that he spent 45% of his time preparing data and then using it to develop models and visualizations, according to his Anaconda Data Science Survey in 2020.

Data scientists can benefit from RPA developers

If a data scientist is in trouble, an RPA developer can help. Data scientists can benefit from RPA developers in the following ways:

Creating metadata: When combined with process mining, software robots leave data trails as they complete tasks, making processes more understandable to data scientists.

Accessing legacy structures: Software robots work with legacy structures to make records formerly locked up in antique gear accessible.

Keep data consistent: RPA developers can decompose large datasets into usable components, organize labels, and cleanse disparate data into a coherent whole.

Implement pre-built AI modules: RPA developers can take the help of available use cases of AI and ML instead of data scientists building models from scratch.

AutoML saves time: With the help of AutoML, RPA developers can determine the accuracy of predictive models saving data scientists' time from building and testing multiple models and leaving them to work on more complex tasks.

If you are a company and you should opt for Data Science Consulting before making up your mind, we recommend hiring an outsourcing company that also offers RPA developers. These benefits not only improve the lives of data scientists but also enable them to accomplish more than they could before. RPA developers enable data scientists to complete their tasks faster and more effectively while facilitating the deployment of the final solution.

2022's Top 5 Robotic Process Automation Tools

Many executives want to use RPA technology to increase efficiency and profits. If you're looking for a robotic process automation tool, here is the list of top RPA tools to consider in 2022.

  1. BluePrism
  2. UiPath
  3. AutomationAnywhere
  4. Pega
  5. Kofax

Bottom Line

Establishing data science and process automation departments is one way for organizations to begin their digitalization journeys. To ensure collaboration between the two departments, institutions must define clear responsibilities, bring in the right people, and implement common working frameworks. Hire data scientists and RPA developers, assign them responsibilities, and sit back and watch the magic.