Press Release - Big data analytics will create a new third wave of M2M but there are challenges to overcome

To maximise its opportunity in this third wave of M2M, any member of the ecosystem will have to adapt to the new data- and application-centric environment and the intrinsic issues of data use, management and ownership

Big Data is set to transform M2M/IoT in a new, third wave. The first wave in M2M involves device-centric solutions, focused on sensing and monitoring. The second wave is more process-centric and enabled intelligent and automated processes. The third wave will be focused on applications and data, particularly in the domains of Subnets of Things (a precursor to Internet of Things) and data communities. To meet the requirements of the third wave, service providers need to develop and manage applications and data analytics to a much greater extent as well as understand how data from M2M may change underlying IT infrastructures. These are the findings of a major new report “Creating value from data analytics in M2M – the Big Data opportunity” published by research and consulting firm Machina Research.

Global M2M connections are growing rapidly, and are expected to reach 18.5 billion in 2022. These connected devices will generate a significant amount of data linked to a diverse range of business sectors and processes. As such, M2M will be one of the major sources of data for so-called ‘Big Data’ analytics. Done right the benefits of stitching together M2M and data analytics will be substantial, for example in reducing inefficiencies and optimising productivity from resources in operational environments, preventing fraud and financial loss, and enabling the development of new products and services. M2M data enables a new set of business improvements, leveraging real–time and extended behavioral insights into new and tangible benefits (as illustrated in the Figure below).

However, as Author Emil Berthelsen identifies, there are challenges ahead: “To extract the maximum value out of Big Data in M2M will involve the handling of huge amounts of structured and unstructured data (as well as metadata), managed in real-time, and processed to deliver meaningful and useful insights of significance and value. That’s not going to be easy.”

The report identifies numerous issues that need to be resolved by those hoping to benefit from this evolution. One relates to finding the best way to identify the value of data. Machina Research proposes a system based on significance, measured in terms of a Data Significance Factor (DSF).

Another potential banana skin is how to manage the data that is being gathered. Commenting on the latter issue, Berthelsen said: “In Big Data, service providers and enterprises will be required to address new and growing responsibilities around active and passive data management including, though not exclusively, the areas of ownership, privacy, transparency, storage and security. These areas become even more important and scrutinized when businesses consider monetizing data. The consent of data owners and the transparency of how that data will be used emerge as two key responsibilities of enterprises. These responsibilities may be partially addressed by emerging technology requirements and developments in policies of ‘fair use’ where data may be used without the consent of users at every instance.”

These, and numerous other challenges associated with Big Data analytics in M2M, are addressed in the report.

For more information on the report, click here. The report is available as part of the Machina Research Advisory Service. For more information on getting access to the service click here. To download a PDF version of this press release, please click here. If you would like to follow up with the author you can do so via email.