John Marney:
Hello and thank you for joining us for another RPI Consultants Webinar Wednesdays. today our topic is system and database maintenance best practices. These are recommendations that apply broadly to just about any application. However, we have pulled this information from our knowledge and experience across the Perceptive, Kofax, and Hyland products.
So first, let’s take a look at our upcoming webinars schedule. Today we actually have two more webinars. At one o’clock central we have Perceptive Experience Content Apps. This afternoon, Mike and I will be back with you discussing strategies on how you can migrate your enterprise content and data into the cloud. That’s going to be a really good one, so please join us for that. Next month we have a Kofax themed webinar series, what’s new in Kofax TotalAgility 7.6, in the morning on November 6th, and in the afternoon talking about what’s new in Kofax ReadSoft Online. Both have had major updates recently.
If you haven’t joined us for our office hours, that’s a little bit different kind of webinar where we take a deep dive into a more technical topic. Those are on the third week of the month. So, Friday, October 16th, I can read that, Perceptive Content application plans and then in November we have a deep dive in the Perceptive Experience.
So many of you probably already know us, but my name is John Marney, I’m the Manager of Solution Delivery at RPI. I oversee our Content and Process Automation practice. That’s us. I’ve been the Software Automation Architect for around 10 years now, and I don’t take it lightly, but I call myself an AP Automation guru so please feel free to reach out about your AP automation needs.
Michael Madsen:
Hello, I’m Michael Madsen. I’m a Lead Consultant with the RPI office, primarily work with Brainware and Perceptive Content solutions dealing with back office and higher education. Also, the office Dungeon Master so we’ll roll this off with an initiative check.
John Marney:
So our agenda today, we’re going to actually break down our recommendations based on different types of applications, different types of servers. So, you have your application, your web, your dat