IoT is an important business enabler, and the better an enterprise can manage its IoT data, the better its business outcomes will be. Connected devices produce gargantuan amounts of data, and businesses need to identify the use cases that deliver business value. This will help them build a robust data strategy.
According to Gartner, enterprises lacking experience in adopting IoT-based digital technologies must have a well-defined strategy and a metric to measure success. IoT leaders must work with business stakeholders to ensure that outcomes align with the strategy. This, however, comes with its own demands. Enterprises will need to improve how they manage data and new technologies while acquiring significantly different staffing and skillsets.
Therefore, it is no surprise that most enterprises work with partners to implement IoT projects. They can advise on a range of topics, including choosing the right hardware, connectivity and security, along with how to apply artificial intelligence (AI) and machine learning (ML) to provide the required data insights.
Seven tips for building an IoT data strategy
Orange company The unbelievable Machine Company ran a recent webinar, Why data determines your IoT project journey, which looked at how to handle, secure and optimize data within an IoT project. Franziska Kühn, Senior Data Engineer and Paul Kerspe, IoT Hub and Senior IT Project Manager, shared seven tips on creating an effective plan to translate data into actionable intelligence.
1. Map your data to your use case at the beginning
Getting data from connected devices is a complex process. You need to work out what you want to achieve with the data before mapping the IoT system. This includes looking at who will maintain the data and who will consume it.
2. Plan and create your IoT architecture
Setting up a secure and efficient IoT architecture requires a combination of building blocks to get the best out of the solution, starting with centralized IoT application instances and an IoT gateway. These take care of the IoT data flow and provisioning, for example.
3. Overarching data management is core
There are many questions to be asked from IoT data, which is why data management is crucial. IoT projects deal with diverse amounts of data in different formats, process it, store it in real time and, if required, build historical data insights from it. These are all common to IoT implementations.
4. Decide on data storage
Data storage is a key consideration in a data management strategy. Unfortunately, data storage isn’t one size fits all. IoT leaders need to decide if they want to filter it and send it to the cloud or store whole data histories in data lakes or a data mesh. Data lakes store data in its raw format, while a distributed data mesh architecture enables users to access and query data from any data source. Data retention policies and regulations must also be considered.
5. Assess data volumes
Factoring in data volumes and real-time capabilities comes with the use cases. Video streaming, for example, takes up much more capacity than sending soil temperature results for analysis.
6. Adopt end-to-end encryption
Security is central to any IoT project as enterprises need to ensure that corrupted data is not getting into the system or being manipulated. Lack of encryption is one of the biggest issues facing IoT data collection and transfer. With no encryption, malicious actors can easily siphon off passwords and other sensitive data. Data should be encrypted for every transmission.
7. Collect only data that you need
Finally, this may seem obvious, but only collect data that is necessary. Enterprises often hoard huge amounts of IoT data and only use a small percentage of it. This creates complexity and cost. It is important that IoT leaders work with business to work out what data needs to be collected to meet objectives and filter it out accordingly.
Find out more about handling your IoT data and successfully initializing your IoT strategy. Listen to the full webinar here.
Jan has been writing about technology for over 22 years for magazines and web sites, including ComputerActive, IQ magazine and Signum. She has been a business correspondent on ComputerWorld in Sydney and covered the channel for Ziff-Davis in New York.