We get a lot of questions from those who want to learn to be RPA programmers. There is a few good trainings we have noticed and categorized according to the providers:
Online education providers
RPA software companies
UiPath’s Community Edition is one of the top free RPA solutions and they have an extensive training package to build UiPath developer community
Though Automation Anywhere is not freely available, Automation Anywhere University offers online trainings.
WorkFusion Express is a relative newcomer as a free RPA solution but already has a vibrant community of developers and a digital training academy: WorkFusion Automation Academy
We had a chance to interview Martin Schmitt, co-founder and CEO of CarLabs and his team. They explain in detail how and why chatbots should be embraced by automotive companies.
Would be happy to hear the founding story of CarLabs. Why did you choose to focus on the automotive industry?
Martin has been a car nut since birth. After a successful career in technology, leading engineering for Shopzilla and others, he finally fused his passion for cars and technology and founded New Cars.com New Cars is a new car lead generating platform that was acquired by one of the largest car shopping portals Cars.com in 2005 for $20 million. Leveraging the auto industry experience gained from Newcars.com and cars.com Martin and co-founder Uzi Eliahou founded CarLabs.
That depends on your company’s automation needs. So it is impossible to answer this one objectively but I will answer a similar question: Which is the best funded RPA software provider?
This is a good proxy for success as investors are looking carefully at the RPA space and are betting on companies’ success with their money. So the best funded vendor should be the one that stands to profit most in the long run.
So we looked at the RPA software providers with top funding:
BluePrism: $155M with $55M from previous investors and $100M from their post-IPO placing.
By 2020, it is expected that there will be between 20 and 30 million IoT units in the marketplace, according to a study conducted by Gartner. With this much data being collected, the need for a way to analyze it grows exponentially. Many of the enterprise applications for IoT analytics, such as in manufacturing, finance, telecom, healthcare, and others have unlimited potential when data is managed and analyzed correctly.
To meet this need, IoT analytics has emerged as the broader category of uses and applications designed to help analyze the data obtained by IoT sensors. Once this data has been properly analyzed it can then be used to help make better, data-driven decisions for organizations that are in search of a competitive edge.