The Three Most Important IoT Data Trends and What They Mean for Technology Leaders

by Equalum

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November 15, 2017 4:40pm


IoT Data Trends

For leaders in the industrial and manufacturing sectors, remaining globally competitive involves navigating a rapidly-changing technology landscape. Here are three of the most defining trends shaping the industry over the coming years – and how technology leaders can stay ahead.

Trend: Growth of data volume, variety, and velocity. Experts refer to these as the “3 Vs” of big data. Simply put, big data is getting bigger at a rapid rate – with 90% of the world’s data generated in the past two years alone. Increasingly, this data is machine-generated. Sources estimate that data generated from machines – servers, sensors, industrial equipment, and more – is growing at 50x the overall growth rate over the coming years.

What it means for technology leaders:
Any system that is going to ingest and move vast quantities of data around the enterprise must be engineered for scale and performance. Batch ETL processes that work well on limited data sets (e.g., nightly loads of transaction data) are often ill-equipped to handle exponentially larger data quantities. This is especially true when those data sets are being generated by more systems and in more varied forms than ever before.

Trend: Transformation of big data into a driver of business growth. Savvy enterprises recognize that the information generated by their operations can be a differentiator – and they are leveraging data in new and often unexpected ways to power business growth. A Japanese real-estate company, for example, was able to create a predictive model for lease renewals based on machine data from their elevators. This trend reflects the “democratization” of data, with a more varied set of stakeholders throughout the organization mining data for critical business insights.

What it means for technology leaders: As a critical piece of infrastructure for driving business decisions, an enterprise’s data ingestion solution must be focused on time-to-value: seamlessness of integration, turnkey support for adding new data sources, and ease of maintenance and use. One of the struggles that leaders in the industrial and manufacturing space have experienced with open-source implementations is that these otherwise-promising frameworks are unwieldy, difficult to work with, and user-unfriendly. These challenges often lead to massive scope and cost overruns both in the implementation and maintenance phases.

Trend: Deep integration of real-time insights into day-to-day operations. Leveraging data in real-time has quickly gone from a pipe dream to a reality, with IoT enterprises leading the way. Common use cases in manufacturing include combining machine data with inventory and pricing data to drive just-in-time parts delivery, leveraging sensor data to power predictive maintenance, and optimizing industrial data through the use of digital twins. Examples abound in other industries as well, including real-time fraud detection in financial services and ad personalization in retail.

What it means for technology leaders: Data ingestion flaws that are merely bothersome at a daily or weekly batch pace lead to crucial process breakdowns and leaky data pipes under the pressure of a real-time environment. A data ingestion solution must be precision-designed for the demanding real-time needs of the enterprise – meaning that it is responsive to the most exacting standards of security, uptime, and monitoring.

    Forward-looking technology leaders are seeking a solution that’s built for these realities of the new data age – a technology, in other words, that can “manage small and big, unstructured and structured data, batch and real-time streaming, on-premises and cloud or hybrid deployments, and deliver trusted data in a self-service fashion to everyone from business analysts to citizen integrators” (Gartner).

    How Equalum can help

    Equalum’s Data Beaming platform is a breakthrough technology, built to help technology leaders stay one step ahead of these industry trends by seamlessly teleporting data within the enterprise in real-time. The technology works by ingesting data in real-time, as it is created, from any number of data sources – then processing and transforming the data before beaming it to any number of target applications or systems.

    Ultimately, Data Beaming technology represents the next phase of data ingestion: a technology that brings together the enterprise design of traditional ETL with the power of open-source frameworks.

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