Data Integration Strategy

The Internet of Things (IoT) offers many opportunities and a new world of data management and security challenges for organizations. First, IoT changes the breadth of what we connect regarding the type of devices. These devices could be as simple as a sensor or as complex as a supercomputer. The move to mobile and IoT means IT Managers must support a broad range of operating systems, various device protocols and multiple types of wireless networks. For example, there are new wireless networks to support IoT such as Long Range Wide Area Network (LoRaWAN) and Ultra Narrow Band. There is also a wide range of protocols and messaging systems that extend from legacy systems such as Supervisory control and data acquisition (SCADA) to the Message Queue Telemetry Transport (MQTT) that targets device data collection and messaging.

One of the exciting areas of the IoT is its potential to change how we engage with technology and transact business. The move to IoT is providing unprecedented access to data that either didn’t exist before, or was too complicated and expensive to collect. While the Machine to Machine (M2M) era focused mainly on the challenges of connecting devices, the IoT era concentrates on the opportunities presented to businesses who use connected data. This data can provide valuable context for business processes. By collecting and analyzing IoT data, groups within an organization can increase efficiencies with services such as predictive maintenance and route optimization. It can also improve the customer experience by supporting new service experiences such as omnichannel retail and smart home applications.

Cloud computing plays a huge role in IoT

Cloud computing will play a huge role in a company’s IoT strategy. Similar to the mobile market, the cloud provides a set of foundational tools for IT and Operational technology (OT) executives to build new applications, services, and insights based on IoT data. Cloud-based tools allow companies to develop, test, secure and connect various data sources into a multitude of applications and business processes. For example, a rich PaaS layer in the cloud provides a set of middleware, security, application components and analytics tools that companies can use to build IoT solutions. Additionally, the cloud offers messaging brokers that can connect and gather data from devices with different protocols as well as functions to integrate IoT data with on-premises data sources and cloud-resident SaaS apps. Cloud services can play a role in securing IoT by authenticating and brokering requests for data from applications to devices. Cloud vendors also offer analytics services spanning from business intelligence dashboards to streaming analytics, to machine learning on demand.

Data integration and analysis

Data integration and analysis are two areas where most IoT strategies fall flat. Access to data isn’t the same as insight. Data must be collected, analyzed and inserted to your existing applications and business processes to make it useful. Companies need both a process and technical plan to turn this data into insight. The process strategy centers on evaluating what business processes and applications can be improved with new data sources and defining how a company’s workflows will change as a result of new information sources. Additionally, companies need to decide what types of third-party data it wants to use to augment its internal data resources. The technical strategy included items such as understanding how to connect data using API platforms, how to select a big data storage solution and what type of analytics to use. The cloud can provide a role in each other these areas. For the purpose of this article, I’ll focus on the data integration aspects.

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Why IoT Needs A Data Integration Strategy


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