RPA Developers and Data Scientists: A Perfect Team!
by Monomita Chakraborty
April 20, 2021
Working with a data scientist, an RPA developer can simplify much more critical procedures than working alone
Robotic Process Automation and Data Science have a mutually beneficial and completely equal relationship. RPA bots could use insights from the advanced analysis of data science to demonstrate punctual behavior and give the bots more knowledge and business relevance.
The automation of RPA has recently moved into the field of data science. This is part of a larger trend toward digitizing data science that includes self-service analytics tools, machine learning, and visual frameworks for building predictive models.
In particular, RPA efforts are supported in two ways. The first involves a variety of AI techniques such as deep learning, natural language processing, and computer vision. RPA can also be used to automate key aspects of the predictive model development process, e.g. B. Choosing the best algorithm for completing and implementing work processes.
Let’s take a look at what data scientists and RPA developers are doing
The primary responsibility of a data scientist is to manage and analyze large amounts of data using bespoke analytics tools so that stakeholders can make rational business decisions. A data scientist typically performs a variety of tasks. However, there are some basic responsibilities:
- Huge amounts of unstructured and structured data are collected and converted into a more readable format.
- Uses a variety of programming languages to get benefits and insights from the data, such as: B. SAS, R and Python.
- Distinguish data trends and patterns that could help a company become more profitable.
- Use data-driven approaches to find solutions to business problems.
RPA developers support companies in the design, development and implementation of RPA systems (Robot Process Automation). You set up and evaluate automated business activities using various automation tools such as Automation Anywhere and UiPath. You will be responsible for a variety of roles for the company, including:
- Develop the automation functions according to the organizational requirements of the company.
- Trying to solve automation-related problems by coding and scripting with any RPA tool.
- Offer experience in device architecture and integration.
- Use tools to configure the latest automation.
RPA developers and data scientists rise as a team
Typically, the two teams that can solve different complex data problems, RPA developers and data scientists, don’t work together. Data scientists and RPA developers have compatible skills. New workflows that use both can be configured with the right administration. In this case, it is possible to scale machine learning faster, free up data scientists for more demanding tasks, train RPA developers, and leverage both teams effectively in terms of business outcomes.
The benefits RPA developers and data scientists can bring to companies are greater than the number of their sections when leaders bring them together. Working with a data scientist, an RPA developer can simplify much more critical procedures than alone, and a data scientist working with an RPA developer can work faster and focus better than ever before.
Even if managers can bridge the gap between these teams, they can uncover enormous opportunities for their company. To do this, managers must enable data scientists to communicate their needs to RPA developers and enable all teams to work together to get better results on complex problems.