A new paradigm is emerging to confront a critical business challenge: how to access and distill vital data that lives in multiple systems that don’t talk to each other. Driving this new model is the industrial IoT, which is leading to new ways to control system architectures, data repositories, and communications systems to interact.

Historically, OSIsoft’s PI System has played a vital role, working with SCADA and MES architectures on one level with control systems sitting below and enterprise systems above.

Now, enterprises are turning to IoT platforms and significant public clouds, such as Azure and Amazon Web Services (AWS), to meet the need for processing power and storage (including time series data). Other companies, such as Foghorn, are pursuing edge analytics. In this approach, an automated analytical computation is performed on data at a sensor, a network switch or other device, instead of waiting for data to be sent back to a centralized place. In between these two approaches are vendors, like Seeq, focused on analytics on top of time series data.

OSIsoft has the potential to bridge these approaches. It has developed integrators for streaming data to cloud platforms while also recruiting analytics and edge companies to build on top of it. In this effort, Microsoft, Foghorn, and Seeq are partners.

Yet, there is no one-size-fits-all approach or one winner-take-all. Different models satisfy different business needs, though they share a common objective: holistic analytics. This moment calls for new thinking and a willingness to break long-established comfort zones. The holy grail? Extract volumes of data residing in disparate systems and convert it into real-time, actionable insights in the context of industrial IoT. Today, only 5% of the collected field data gets used effectively to improve the business. 5%!

Enterprises swimming in data need a fully integrated ecosystem to destroy data silos and arm stakeholders with tools for visualization and data-driven planning. The recent collaboration between AWS and OSIsoft creates a data collection behemoth that tries to bridge two worlds: IT and operations. However, how do you harness the power of all this data in a way that is customizable to meet the needs of your business?

Enter rapidBizApps (rBA). Let’s explore 4 important ways that rBA can help businesses move the needle on that 5% data-usability statistic:

1. Because its core business is mining, rBA has the capacity and the expertise to help mines digitally transform their business. Its technical team is dedicated to the principle that technology alone is not enough; you must empower your staff with easy-to-digest analytics to inform decision making. Partnering with rBA is akin to calling in a specialized doctor to treat a complicated medical condition. For mines and oil fields, rBA is that specialist.

2. rBA’s products, specifically groundHog and rapidInspect, integrate with AWS. Yes, the AWS-OSIsoft collaboration pairs the best operational technology platform (PI Systems) with the best information technology platform. However, that’s not enough. To optimize value to the customer, integration services and technical consulting resources are required. rBA provides both, delivering predictive and actionable analytics that streamlines production and improves the bottom line. For mines and oil fields, the ability to leverage data is the only way to formulate strategies that will propel operational and business performance.

3. Break down the silos and migrate the data. In mines and mills, the data collected by thousands of sensors is sent to a data historian: OSISoft’s Pi. All this data sits within site on a system somewhere in a cubicle or the site’s computer room. rBA helps enterprises integrate the data using a federated database. Relying on machine-learning algorithms, rBA migrates data from silos and from behind firewalls to Amazon Storage clouds. From there, rBA can help you extract the value in ways that are specific to your business.

4. Amazon’s SageMaker makes it easier for data scientists to build and deploy machine learning models. The brilliance of SageMaker is that it creates opportunities for all data scientists, not just those employed by huge, resource-rich businesses. rBA has leading-edge tools that provide users with numerous insights into the data. Technical personnel familiar with PI are typically not familiar with operating AWS, and vice-versa. But rBA’s tools bridge this knowledge gap. For example, AWS requires a burdensome configuration; rBA does the heavy lifting for you.

3 Key Questions

By the end of 2018, integration — various system components and back-end systems — will account for half the cost of deploying IoT solutions. The potential value of industrial IoT is unquestioned. But too many enterprises are sitting on mountains of raw data merely because they lack the expertise to derive actionable insights from it. Before an enterprise commits to an IoT implementation, it must answer three critical questions:

Q1. What are the fundamental integration challenges?

Q2. What complications can you expect if the project’s scope expands?

Q3. How will IoT tax existing integration skills and resources?

IoT holds the promise of transforming your business, but it also poses a huge opportunity cost. If your implementation lacks integration and careful planning, you risk losing your competitive edge. rBA has the expertise, integration tools and services to help you keep — and sharpen — that edge. Are you ready to start a conversation? Or request a free demo?


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