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Data collected from the physical world by digital Industrial Internet of Things solutions can bring enhanced productivity and customer utilization—only if that data is properly managed and stored. Industrial Internet of Things (IIoT) solutions enable users to improve their decision making and enhance systems usage optimization. Such deployments generate large quantities of data that needs to be processed and analyzed in real-time. The sheer volume and structure of data collected via these solutions’ hardware devices challenge conventional data storage methods.
We’ve outlined 3 key steps to take when defining the data storage requirements of IIoT solutions:

1. Establish a flexible data storage system that can scale to meet your data streaming needs

Businesses that require real-time business process support from their IIoT systems will need to scale fast enough to transfer the entire collection of raw data being generated to and from a location. Companies delving into IIoT should plan for the possibility that their solution could realistically grow to generate terabytes of data as user adoption increases. IIoT machines generate two distinct types of data–large-file data (ie. photos & videos), and tiny, log-file data from sensors. These sensors can generate billions of data points that must be digested and securely stored. Whichever data storage system you choose, it should be capable of storing billions of data points without ballooning costs. Cloud storage systems are best poised to meet these flexibility, scalability, cost and security needs.

Just as IIoT devices are spread across distributed environments, the data being generated should be stored in distributed mini-data centers to avoid bottlenecks. You’ll need datacenters that are designed to handle large-file sequential I/O and small-file random I/O. This will give your IIoT system the bandwidth to support real-time processing of large data streams through multiple data ingestion points. Initial data processing can occur at these mini-data centers, and then be transferred to a central site for further data processing. Ultimately, your data storage system should be able to flexibly accommodate increases in data storage needs associated with adding new devices or expanding your userbase.


2. Consult your business objectives when mapping out your data backup procedure

A well-defined data retention policy will be essential to the success of your IIoT deployment. Previous efforts spent defining the business objectives of your IIoT solution should guide you in selecting which data streams should be extracted, backed up and stored for extended periods of time. This automated backup policy will decide which data is valuable enough to be retained, or should be purged.

Some of the machines and devices connected to your IIoT system may also store data internally. Systems administrators will need to identify whether the data these devices collect will need to be backed up onto your IIoT solution’s back-end server.


3. Choose a secure cloud storage vendor to meet your compliance needs

Many industries have codes and regulations specifying how to protect data transmissions and securely store data. Privacy and compliance are major concerns for industrial organizations. Many cloud-based storage systems are available that adhere to even the strictest industry regulations. CareCloud, for instance, offers HIPAA compliant cloud storage for strictly regulated medical enterprises.

Data storage can balloon into a major challenge for your organization if not planned in detail prior to launching your IIoT solution. This is not a step that should be delayed or approached in an ad hoc manner. What other questions do you have on establishing data storage requirements for your Industrial Internet of Things Solution? Comment below!

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