The Computer Weekly Developer Network team is at UiPath Forward IV 2021 and that means three things: UiPath news and insight into the latest streams driving Robotic Process Automation (RPA); a Covid-safe approach to the new world of how tech conferences are staged… and, thirdly, partner commentary.
California- and New York-headquartered Alteryx (pronounced al-trix, not al-ter-ix) describes itself as an Analytics Automation (AA) company.
What happens when AA meets RPA? We’re glad you asked.
A new Alteryx-UiPath connector (by which the firm means a piece of dedicated tooling software tasked with capturing, managing and directing discrete application processes) has been produced to automate end-to-end analytics processes… presumably, ones that are ripe for (or already feature) good application points (as in deployment targets, not as in ‘app’) for RPA to exist.
This is not just automated analytics with RPA efficiency for connected modern cloud-native systems, Alteryx and UiPath have ensured there is enough reverse engineering competency here to also apply this technology to legacy systems and what the firms call ‘non-API sources’ as well.
As well as some warm fuzzy ‘bi-directional integration with UiPath’, Alteryx promises to help continue efforts designed to modernise enterprise infrastructures, especially where data has remained trapped in legacy systems and other sources that lack the necessary APIs for access.
Suresh Vittal, chief product officer of Alteryx says that thanks to RPA, organisations with repetitive processes involving data residing in homegrown, older, or non-API systems can now achieve faster time to insights and reduce the risk of error.
“The newly released connector accelerates value for mutual customers by making it easy to invoke UiPath bots from within an Alteryx workflow, enabling automated analysis and augmented robotic intelligence to drive smarter business outcomes using every byte of data in the organisation – even the ‘dark’ data hiding in legacy systems,” said Vittal.
Alteryx is now capable of calling on a UiPath robot to fetch and deliver data to dark data sources. The promise (if it all works) is rapid, automated analysis at scale rather than teams having to work through slow and error-prone manual processes.
No legacy loitering
By automating operational analytics, analysts and other knowledge workers can focus on value-added activities and analysis instead of spending time manually retrieving and processing information from legacy systems.
The team was able to take a legacy system capable of processing just a few thousand applications, to over two million applications using Alteryx to train UiPath bots that sorted and backdated millions of pages of paperwork.
Bots are good, but they need a GPS
It appears then, that bots are good i.e. they go and do the jobs they need to do, they get better at their automation responsibilities as they go and they learn more (and suffer fewer instances of ‘human handoff’) and they can be applied to more application and data service topographies as they become increasingly sophisticated… but as good as they are, they can benefit from some virtual GPS orientation in the form of analytics automation to help them get to the right place at the right time and open doors that might otherwise be closed.