As cloud suppliers continue to grow their footprint in the IoT value chain, their investments in data and analytics services are accelerating.
Based on the review of cloud vendor offerings, recent acquisitions, and competitive outlook, tech market advisory firm ABI Research forecasts that cloud suppliers will grow their share of IoT data and analytics management revenues from $6 billion in 2019 to $56 billion in 2026.
While the growth is impressive, cloud vendor’s services today are focused on data management complemented by a generic analytics toolset. Cloud vendor’s revenues come primarily from streaming, storage, and the orchestration of data.
Analytics services across cloud vendors, on the other hand, are less differentiated, as reflected in pre-built templates such as AWS Sagemaker and Microsoft Azure Notebooks which leverage the open source Jupyter project. Considering that many cloud vendors are in the early stages of analytics investment, cloud vendors are relying on their partners for addressing more specific advanced analytics and vertical market needs.
“The overall approach shown by cloud suppliers in their analytics services reflects the dilemma they face in the complex IoT partnership ecosystem,” said Kateryna Dubrova, research analyst at ABI Research. “Effectively, do they rely on partners for analytics services, or do they build analytics services that compete with them?”
Interestingly, streaming is the one analytics technology that all cloud vendors are building into their solution portfolios to blend data management with near-real-time analytics on streamed IoT data.
AWS, Microsoft, Google, IBM, and Oracle, for example, are promoting their proprietary streaming solutions to differentiate, accelerate time-to-market, and win over customers.
In contrast, companies like Cloudera, Teradata, and C3.ai are introducing streaming analytics services heavily reliant on open source technology, such as Spark and Flink.
However, by focusing on data management and streaming technologies, cloud vendors are ceding the advanced analytics market to other suppliers. Hence, the advanced analytics market is an excellent example of the “coopetition” in the IoT ecosystem, where cloud vendors are partnering with advanced analytics suppliers.
This coopetition enables them to promote an end-to-end IoT technology stack, for example Azure and AWS have partnered with Seeq to leverage its advanced analytics capabilities.
At the same time, other vendors such as Oracle, Cisco, and Huawei, are pushing intelligence and analytics closer to the devices, expanding their edge portfolio. Such divergent analytics strategies represent the reality and challenges for serving a very diverse IoT ecosystem with IoT analytics services.
“Ultimately, businesses are moving to an analytics-driven business model which will require both infrastructure and services for continuous intelligence. Cloud vendor strategies need to align with this reality to take advantage of analytics value and revenues that will transition to predictive and prescriptive solutions,” Dubrova said.