This study focuses on the global edge analytics software market. Edge analytics solutions utilize devices such as routers, sensors, integrated access devices (IADs), and multiplexers to sift through and rank large amounts of data. Edge analytics software analyzes data on the device, reduces latency, eliminates the need for large amounts of data transfers, maintains data privacy, provides real-time actionable insights locally, reduces cost, and increases scale.
Several Big Data analytics (BDA) vendors expand their product portfolio to include edge analytics solutions and provide insights in real-time, rather than moving data to a central hub for analysis. Edge ecosystem vendors collaborate to push the technology forward and compete to gain first-mover advantage across industry verticals and locations.
There is a consensus that a single vendor cannot deliver on all future use cases; collaboration is becoming the key to market expansion. Key revenue contributors in the market include SAS, C3.ai, SAP, Rockwell Automation, and FogHorn Systems. Other market vendors include Swim.ai and Guavus. Edge vendors such as Siemens, Intel, SiSense, and NVIDIA are still piloting edge software solutions driven by use cases; however, they have not been included in the analysis this year. Additionally, IBM, Microsoft, and Amazon Web Services (AWS) provide open-source solutions or software development kits to support the developer community in creating edge analytics solutions.
The need for real-time insights drives market growth. In manufacturing, factories are dependent on uptime; to predict machine maintenance needs, they process data on the edge to avoid bandwidth and latency issues and draw real-time insights for timely action. The market is also affected by organizational competition, dissatisfaction with BDA solutions, and the new revenue generation through data monetization. However, the market has been unable to reach its full potential due to insufficient data hygiene, difficulty proving return on investment, data security challenges, lack of data standardization, and a shortage of skilled labor.
Readers who will benefit from this research include vendors from the edge analytics ecosystem, advanced analytics, data discovery, and visualization sectors. Organizations looking to understand or enter the edge analytics market and vendors across the manufacturing, energy, logistics, telecommunication, and transport sectors will also benefit from this research service.
Key Issues Addressed
Is the market growing? If so, how long will it continue to grow, and at what rate?
What are the regional trends in the edge analytics software market, and what are the implications for vendors' global growth strategies?
Are the products/services offered today meeting customer needs, or is additional development needed?
What are the critical success factors? Who is further along the curve in addressing these issues?
What are the major drivers and restraints in the edge analytics market?
Which vendors are leading the market, and what do vendors need to know to stay ahead of the curve?
What are the key trends, and how will they impact the edge analytics market?
Which market segment is growing faster?
Key Topics Covered:
1. Strategic Imperatives
Why Is It Increasingly Difficult to Grow?
The Strategic Imperative
The Impact of the Top Three Strategic Imperatives on the Edge Analytics Market
Growth Opportunities Fuel the Growth Pipeline Engine