SaaS Deployment

The Best-in-Class Hybrid Solution for Industrial Analytics at Scale

Driven by a business need to remain competitive, organizations have heavily invested in digital transformation programs. This includes employing Software as a Service (SaaS) solutions. The aim of these initiatives, including SaaS deployment, is to make better use of existing business assets while reducing the time it takes to gain value from data. Digital transformations foster data-driven decision making, which allows a company to remain competitive in challenging market conditions.

In a hybrid world where people work remotely and on-site, companies also must offer greater flexibility to access data while maintaining the highest level of data security and performance standards.

The adoption of cloud technology plays an important role in a digital transformation. A cloud solution offers greater agility and lets more people access business data faster. Meanwhile, process manufacturing companies must be able to analyze, monitor, and predict the performance of their manufacturing processes at scale. Cloud-first solutions offer this flexibility, which makes them ideal for global engineering or operations teams that need to manage multiple assets.

What is SaaS Deployment?

In general, deployment refers to the process of making a system or application available for use. There are three types of deployment to consider for industrial analytics software.

  1. On premises: This is a more traditional installation. The software is loaded on actual or virtualized hardware within the plant. This deployment traditionally coexists with data stored in on-site historians
  2. Private cloud: Organizations can install the platform in their own hyperscaler cloud environments (e.g. through the AWS or Azure marketplaces)
  3. SaaS: In the SaaS model, the platform is fully managed by the vendor and access is offered at a subscription rate

Organizations may have specific reasons why they select one option over another. When it comes to flexibility, however, SaaS is the ideal choice. It lets companies reap the benefits of high-performance industrial analytics at the right scale, and with minimal IT overhead. The solution works equally well for companies starting small or those rapidly moving to a global level. It also works regardless of where time-series and contextual data is stored: On premises or in the cloud.

While there are a few software deployment options to choose, SaaS offers the most flexible, ready-for-scale solution that also reduces total cost of ownership (TCO). Regardless of where the data is stored, SaaS deployments offer the same capabilities to access data resources securely.

TrendMiner’s SaaS Solution

TrendMiner’s SaaS package, which can easily be deployed in any availability zone in Azure or AWS, was created following years of experience using best practices to develop industrial analytics at scale. The SaaS package includes our core values of Security by Design and Security by Default, which means data is protected in transit and at rest. The package includes maintenance tasks, such as backups, support/troubleshooting, and regular updates. It also offers immediate access to the latest TrendMiner capabilities to ensure the shortest time-to-value for process manufacturers.

Because the solution is offered as SaaS, everyone in the organization who needs it will quickly have high performance access to data from anywhere in the world. TrendMiner’s SaaS also covers an organization’s data protection requirements and those established by local government authorities.

Through integration with an established Single Sign-On (SSO) provider, TrendMiner SaaS mirrors user privileges to provide the right level of data access to the right people at the right time. These could include expert central group users running plant comparison analyses to operators at the plant monitoring equipment in real-time, where each group needs different levels of access.

Concluding Thoughts

As companies adapt their environments to a hybrid or remote workforce, they begin to embark on a digital transformation. A cloud-first strategy is an important part of this transformation. This strategy provides greater agility and faster access to data for more people across the globe. It is ideal for global engineering or operations teams that need to manage multiple assets.

Choosing a deployment option requires many considerations. However, SaaS is the model that offers the greatest flexibility for a process manufacturing company to grow at scale. TrendMiner’s SaaS model offers lower TCO and higher availability, while flexibly allows access to a growing list of time-series and contextual data sources.

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