Petro.ai and Spotfire:  Cloud Tech Differentiators
Passion for Change

Petro.ai and Spotfire: Cloud Tech Differentiators

Rosemary Jackson  •  

Spotfire: Author driven high maintenance dashboards that keep the author and IT busy, work can be done in a cloud option but mostly for delivering a dashboard 

Petro.ai: Single tenant, full cloud, can be peered, no demands on IT, scalable, reproducible by every user because there’s no author

There is a human factor to Industry 4.0. The Fourth Technological Revolution is already here in platforms like Petro.ai that enhance human capabilities and are powered by the cloud. Petro.ai takes the burden of Spotfire authorship off the engineer giving you state-of-the-art dashboards and apps that any user can reproduce. There’s no data to connect; it’s all been loaded and verified. Your full stack is in the cloud. 

“Cloud based is so important, it’s scalable, it’s elegant, it’s connected in with security,” Troy Ruths, CEO of Petro.ai urges, “We can set up large tests on the system and make sure it works well. That’s why there’s been a big push toward the cloud.” Forbes echoes this recommendation, “choosing to transition to cloud-hosted infrastructure and applications is one of the most important and impactful business decisions you will make.”

Spotfire does have a cloud option. But when you’re thinking about moving to the cloud, you need to do your research. There’s more than just doing your job in the cloud. Let’s look at the differentiators.

1. The Bottleneck of Authors

In Spotfire, authors build the dashboards and are responsible for updates. A consumer uses the dashboard. Typically, a consumer doesn’t know all of the deep features in the tool. They might not even understand marking or filtering or visualizations or drill downs.

Ruths explains, “Petro.ai gives you the ability to have your full stack in the cloud. You don’t need authors. A big bottleneck in the Spotfire process is authors. Authors make the dashboard, set up the calculation. It leads to fast analytics, but not analytics that can stick around.”

“It’s the question of having evergreen analytics,” Kyle LaMotta, VP of Analytics adds. “Someone builds a really complex Spotfire dashboard that’s very valuable but as soon as something breaks or needs updating or the data model changes then there’s only one person who knows how to rewire it. If that person leaves or they have other responsibilities, then the dashboard dies out.”

“When we originally started out, we were trying to make tools for authors,” Ruths talks about the early years, “We said, let’s empower this amazing group of people who are authoring all these analytics and sharing it with the organization. What we found in oil and gas is, it’s a pretty small group. And if anything, authors are leaving oil and gas because they can get good jobs in other domains. They can go somewhere where it’s their real job and not just a side responsibility.

“With Petro.ai, we’re taking all these one-off Spotfire dashboards and visualizations and bringing it more contextually to full cloud on the reservoir. I think that’s been a clear winner for sure.” 

2. Data Layer

The cloud eliminates user concern about the data layer. There’s no data to connect. It’s already been loaded and verified. The underlying assumption in all BI tools is that the data’s been curated well and is ready for analytics. LaMotta sighs, “But with Spotfire, that’s always a problem. Which information link am I supposed to use? How am I going to load this database? How am I going to get access to this server? These are always challenges with Spotfire—dealing with the data, then the data model changes and everything breaks.

For Petro.ai, if the data models changes, no one even knows because it’s all under the hood and all the applications are updated to work with the new data model.”

3. Data Representation

For Ruths, addressing this important issue was a strong motivator for the development of Petro.ai, “Spotfire requires data to be in tabular format. But data comes in all varieties. And especially reservoir data. Mashing up different domains, there’s all sorts of joins you have to do in Spotfire to build a specific visualization. In the early years, we spent incredible amounts of time trying to come up with creative joins just so we could visualize it. And in some of those cases, the data shouldn’t be joined, you’re just doing it for a visualization.

When you build a cloud-based technology from the ground up, it means you don’t have to coerce the data into tabular formats. You can keep it in the right format for that data. A good example is the 3D viz. For the 3D viz in Spotfire, we had to make a huge amount of reservoir data tabular. You can do it but it’s easier if you let the data stay in its native format where it can be hierarchical and spatial as in Petro.ai Earth.”

4. Sharing and State

LaMotta highlights, "The issues with marking and setting up all these complex workflows in Spotfire is they’re not repeatable. So, if we were to build two dashboards for a company in Spotfire, the user flow and how they’re interacting with that tool will be a little bit different. And it’s going to be confusing when they try to go from one to the other. 

“In Petro.ai, the workflows are exactly the same, the apps are just different. You start with an input, you use some settings to configure your boundaries for that model and then you run the model. Whether you’re doing a forecast scenario, a frac hit scenario, or a type curve, it’s all the same steps, only the output is different. By having those common paradigms, it makes it easy for the user to try a new workflow. And share both the process and the outcome.”

5. No Hidden Costs

“With the cloud, there’s no need for IT to be involved,” LaMotta understands this issue well. “Typically a new platform that’s adopted by an organization, their IT team has to support it and so must understand the data base. They have to understand how to run updates. They’re like machines keeping those machines up to date.

“Cloud eliminates all of that IT infrastructure and need for IT knowledge. Petro.ai provides the service to keep it up to date. IT doesn’t have to be involved at all. That’s good from their point of view because they don’t have to commit resources to an application. It’s like a hidden cost of software. What is the IT requirement? On our side it’s easier to service an organization if they don’t need IT involved. An engineer can adopt it for free, try it out for a few months, and their IT team doesn’t even need to know about it.”

6. Data and Security

“You have to watch your data and security,” Ruths cautions. “There’s lots of different ways to set up a cloud infrastructure. When we spin up a Petro.ai environment for a customer, it is sandboxed to them. It doesn’t communicate with any other environment. There’s no mixing of data ever, no machines mix that data. That’s very important to us because we’re dealing with sensitive data.

Petro.ai is single tenant, but there are multi-tenant cloud services that can mix data, even in oil and gas. We’re unusual in that we don’t. We make sure that we don’t blend anyone’s data together.”

7. Other Good Stuff—No On-Prem and Great Peer Environments

“I think a couple of points are important,” Ruths leans forward in his zoom frame, “Most cloud applications use a blending of on premise and cloud applications. Petro.ai has zero on-prem. Schlumberger, for instance, is a mixture of on-prem and cloud applications. Petro.ai has zero requirement for on-prem.

“And just moving to the cloud on the surface won’t give you answers. You have to be a savvy buyer. At Petro.ai we’ve thought really hard about what the right structure is for our customers. We can peer our sandbox environment with a company’s corporate one and limit certain access. That allows them to directly connect into our Petro.ai peered environment. Petro.ai is an elegant easily scalable system.”

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