ADLINK Adjusts to Data Sharing in the IoT - Acquires PrismTech to Strengthen its Vortex DDS Flagship

In November 2017 IoT software IoT tool provider PrismTech was absorbed by ADLINK, a data connectivity, Industrial IoT platform and professional services player. PrismTech will now lead ADLINK’s IoT Solutions and Technology group bringing one of its flagship products (Vortex DDS) with it. Vortex DDS is an Intelligent Data Sharing Platform for critical IoT operations assisting system integrators, OEMs, device platform vendors and cloud service providers operating healthcare, energy, transportation, smart cities and industrial automation verticals.

This is a crucial step for ADLINK and one that is building towards a future-looking portfolio in the emerging data sharing and data exchange markets in the IoT. As ABI Research has examined in IoT Data ExChange Services (AN-2415) both established vendors and new market entrants are trying to capitalize upon the “data de-siloing process” that is already underway. From the smart home to enterprise systems, consumer electronics and smart city applications data sharing initiatives are set to transform the ecosystem moving forward.

For ADLINK, while the “data sharing” part relates to already subscribed clients it still constitutes a small but vital step in enhancing the company’s data sharing and exchanging offerings in the emerging IoT ecosystem. More specifically, having a data sharing initiated as part of an Service Level Agreement (SLA) or as part of an overarching cloud service is a great first step.

ABI Research posits that in the future of IoT rests the ability to tap into a grand data pool, generated upon anonymized and aggregate data sources of trillions of devices, sensors, systems and users. Let’s face it, it is no secret that most of companies have quite limited awareness over the treasure trove in their own databases and invest far less than they should in data analytics. Fortune 500 companies, market leaders, and innovative startups are obsessed with their analytics capabilities. However, unless a company operates at the same time across different market verticals they simply cannot appreciate the true analytics and machine learning applications offered by the IoT.

This means that data gathered from every market segment from consumer electronics to industrial settings can not only:

• increase the potential of Big Data analytics exponentially (as well as AI and machine learning applications)
• but also allow IoT vendors to better position themselves
• enable them to make sense of data gathered from both external and internally managed services and devices in a more streamlined manner
• allowing them to gain insight from customers out of their reach before attempting to cross to other verticals, thus empowering the industry

The problem with sharing, exchanging or selling IoT data is, however, burdened by multiple implications. Other than overcoming the barrier of convincing C-level executives that they are getting a bad deal in the data sharing process there are other more technical issues. Cloud service restrictions, consumer data privacy regulations, and data governance policies keep this objective from being realized. Make no mistake though – this is a good thing!

For IoT data exchange initiatives to be successful a common set of rules must be established. Thus, a new set of specifications must be set to describe the notion of “value” for data which must arise (organically if possible) after internal discussions between all involved parties. This concept of data value will differ significantly according to each respective industry and market vertical. This shift cannot be forced upon the IoT in a rapid manner, especially given its recent exploding growth but is certainly one that is bound to take on a more solid form the closer we move towards better machine learning and data analytics applications. A more detailed analysis on this subject can be found in ABI Research’s IoT Data Exchange Services (AN-2415).