The Futurum Group with Qlik at AWS re:Invent 2023 – Futurum Tech Webcast
Steven Dickens www.facebook.com
In this episode, Steven Dickens is joined by Brendan Grady from Qlik to discuss their modern approach to AI implementation and more.
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The Futurum Group
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Transcript:

Steven Dickens: Hello and welcome. My name is Stephen Dickens, you’re joining us here live from AWS re:Invent, and I’m joined by Brendan Grady from Qlik. Hey, Brendan, welcome to the show.

Brendan Grady: Thank you. How are you doing?

Steven Dickens: I’m good, I’m good. We’ve finally got here. We’ve done our 20,000 steps to get onto the show. Let’s get the listeners and viewers orientated. Tell us a little bit about your role and then a little bit about Qlik.

Brendan Grady: Sure, not a problem. So got my name, Brendan Grady, got it right. So, that’s a good start.

Steven Dickens: It’s always a good one to get that, too.

Brendan Grady: Always a good way, absolutely. I’m the general manager of the analytics business unit at Qlik. Qlik is a analytics and data integration company. We’ve been in business for 30 years. In fact, we are celebrating our anniversary here at re:Invent. We had a big party.

Steven Dickens: Congratulations.

Brendan Grady: We had a big party yesterday, strong partners with AWS. We really bring a lot to the table for those customers that want to move their data to AWS. They want to run their workloads in AWS. We’re really are thrilled to be here at re:Invent.

Steven Dickens: So, analytics is a quiet little backwater of the industry at the moment. Nobody’s talking about that stuff. I joke, obviously there’s lots going on. How should people be thinking about you guys in the context of all of the noise and the buzz that’s going on? We’re hearing lots about generative AI, obviously. We’re here at re:Invent and AWS have launched Q. There’s all the stuff that they’re doing with Bedrock as well. Where should we be thinking about you in the context of everything that’s going on in the industry right now?

Brendan Grady: It’s a great question. So I mean, if you think about AI, the buzz around AI, it is here to stay. It is absolutely here to stay.

Steven Dickens: I think we’re only in the first innings of it, I don’t think-

Brendan Grady: Oh, completely.

Steven Dickens: … although this year’s been crazy and every vendor’s been talking about it. We’re still so early.

Brendan Grady: Yeah, and I mean, one of the sessions that I’m running actually later today, oddly enough, we are going to talk about AI. So, where Qlik really fits in is, you really need to think about AI in the context of traditional AI techniques around machine learning, things like that. And then generative is adding a whole other layer there. And so, Qlik can help you get that data that you need to bring into your models. It can help you manage it, manage the data quality, and then it can help you actually identify patterns within that data. And the most important thing is not just the analysis of the data and getting it, it’s what you do with it. So, Qlik and our platform allows you to actually take actions on those decisions, right within the processes that you’re running.

Steven Dickens: So, we hear a lot about data curation, data preparation, vector databases, people getting that data ready. Where should we be thinking about Qlik and what’s the conversations you are having with some of your clients as they start to get ready? I’m hearing small language models, large language models, I’m hearing a lot of this open source space. Where should we be thinking about you guys in that context?

Brendan Grady: It all starts with our customers. So, we’re talking to a lot of our customers. They’ve all kicked the tires on the OpenAI. So, a lot of our customers are realizing that that data isn’t necessarily curated in the way they need it. So, what we’re hearing from our customers is that they look to us around getting access to that data and making sure it’s going to be governed in a way that will allow them to manage the risk for their business. In fact, you’ll actually hear in one of my presentations, one of the missteps customers make is they forget about the quality of the data, especially in generative space.

Steven Dickens: So, you talked about this, the five missteps presentation that you’re doing. Maybe for some people who aren’t at the event, can you give us the precise meaning of that? What are those steps and what should people be thinking about?

Brendan Grady: Yeah, I mean, there are five things we want you to think about. First and foremost, and it’s amazing to me in 2023, I’m having this conversation, you actually need to start with what business problem you’re trying to solve. It’s not technology for technology’s sake.

Steven Dickens: We’re still having that conversation.

Brendan Grady: It’s still happening. We’re still having that conversation in 2023. You need to think about that. Don’t forget about your data. The data and what you’re starting with is critical. It’s not just getting some data. It’s getting the data you need to make some of those critical business decisions.

A third area that we’re really thinking about is don’t forget about traditional techniques. It’s not all generative AI. There are machine learning techniques and other techniques that you want to apply. Always make sure that you’re taking a smart approach to managing that data, constantly updating it, refreshing your models, and then finally, pick the right model for you. If an open model is right for you, do that. If a private model is right for you, do that. If a combination, we really want to embrace that. So, I said there are five, but there’s actually six.

Steven Dickens: You’re going to have to rename your presentation.

Brendan Grady: I am actually, and legal is going to be very upset with that, obviously. The sixth one is, don’t forget about the humans. Keep the human in the loop, it’s sort of like-

Steven Dickens: Is that for validation of the answers? Is that for thinking about a human checkpoint? Is that guardrails? Maybe expand there a moment.

Brendan Grady: It’s an interesting point. There are going to be some decisions where you can just automate them. The risk to your businesses is small. And as you listen to Dr. Jai Ganesh, who’s speaking with me later today, he really talks about the human in the loop, and there are three types of decisions. There are micro decisions that he’s thinking about that … minimal risk to the business. There’s macro but not quite strategic level decisions, macro level decisions where you want to have a human be part of the process, whether it’s from the data prep or analyzing. And then there are bigger ones that they really present a bit of a risk to their business and that’s where they’re keeping the human in the loop. So, to continually train those models.

Steven Dickens: I think that makes a lot of sense. I mean, I think as we say, we’re still at the early stages of this governance hallucinations. These models are improving on an hour-by-hour basis with the innovation that’s going on. But I still think there’s a case for human oversight or governance in a lot of cases.

Brendan Grady: Completely.

Steven Dickens: So, we’re here at re:Invent. You guys are doing a lot with AWS. Maybe just double click on that for a moment and tell us what the partnership and collaboration looks like.

Brendan Grady: So we’ve been an AWS customer for years. We build our cloud platform on it. And from an analytics perspective, one of the more interesting things that we’ve come out with recently is the Bedrock connector. So, Bedrock is a way that we can take advantage of those large language models, and we are actually showing how you can take traditional analytics and dashboarding and everything that goes along with that, bring it into Bedrock and have it tell you a story about your data so that you know where you need to focus. So we’re really, slang term is we’re really jazzed about it. We’re really excited about it. We think it presents a tremendous opportunity for those customers that use traditional BI and business intelligence to combine it with large language models in generative.

Steven Dickens: So, it’s the combination of the stuff you’ve been doing for the last 30 years, but partnering with AWS and the Bedrock solution-

Brendan Grady: Completely.

Steven Dickens: … to take it to the next level.

Brendan Grady: Absolutely.

Steven Dickens: So, as we start to wrap here, what should those vendors and clients and partners be thinking about as they look to partner with Qlik? What would the three takeaways be, the-

Brendan Grady: Three takeaways? Wow, that’s putting me on the spot here.

Steven Dickens: I know, I ask the tough questions.

Brendan Grady: You ask the tough questions. You did warn me about page two.

Steven Dickens: Yeah, that’s on page two that you didn’t see.

Brendan Grady: That’s great. So, the three things that we want customers to be thinking about. Number one, from an AI perspective, don’t forget about your data and think about what it’s going to take. And Qlik can really help get that data, help you curate that data, help you manage that data.

Second thing is don’t forget about some of your traditional business intelligence as well as traditional ML techniques. And third, you really want to do this in a way that is going to not get you locked into a specific vendor. You want to try to be as neutral as you can and work with someone who’s not going to want to own your data. And that’s not us.

Steven Dickens: Well, I think there’s a couple of things there, that optionality is key. I think as we’ve said, we’re at the early stages of this. So, the temptation to over-partner and over-specify and get yourself locked in. The other piece I liked about what you were saying was the ML and the analytics and some of the BI piece. I think everybody’s rushed to generative AI and that’s valid. Everybody’s going to need a chatbot, or a co-pilot, or a Q, if that’s AWS this week. Whatever they’re going to need there, there’s a lot of value still to be had at that AI level.

Brendan Grady: The really interesting angle, we ran a customer event a few weeks ago at our Lund headquarters, and I asked a question. I said, “Who here is interested in AI?” And everybody raised their hand. Second, “Who here would take a meeting with us because we have a story around AI?” Everyone raised their hand. The last question I ask, “Who here is going to build a pretty pivot table and provide that to their end users?” Everybody raised their hand. So, everybody understands they need AI, but they’re all seeing that this is an evolution in their journey, and the people that are going to get it right are going to make it an evolution and make sure that it supports their business in the way that it’s going to help them grow.

Steven Dickens: So Brendan, you practiced the perfect summary to finish our conversation, so thank you for that.

Brendan Grady: Yeah, thank you. Appreciate it.