AoT is a combination of technologies, software and services, tools, policies, platforms, guidelines approaches, and a set of professional services. AoT software and solutions are defined and judged by their capabilities to reduce the overall operational time, cost, and required expertise, to develop analytics-rich AoT applications. The solutions are primarily responsible for collecting, integrating, cleansing, and filtering data from Internet of Things (IoT) sensors and devices. The solutions then apply model-based and datadriven prediction analytics, as well as, optimization and simulation on the collected data, to generate useful information.

The IoT Analytics software market is expected to grow from USD 7.19 Billion in 2017 to USD 27.78 Billion by 2022, at a Compound Annual Growth Rate (CAGR) of 31.0%. Factors such as the tremendous growth of IoT data and the need for advanced analytics and automation of businesses are driving the global market. In the component segment, the IoT Analytics software segment is expected to have the larger market share during the forecast period. The demand for IoT Analytics software is rising as organizations are looking for solutions to generate business-related insights and plan the next steps accordingly based on the insights gathered. Vendors provide software and solutions that assist companies with data collection and data analysis for generating meaningful insights. IoT Analytics software solutions filters the aggregated and enriched data so that it can be analyzed to provide a high throughput from multiple live input data sources. Among applications, the predictive maintenance and asset management application is expected to continue its dominance during the forecast period. Asset management integrated platforms assist users in managing physical assets and tracking equipment performance. The platforms also provide service assurance by enabling real-time alerts and providing automated corrective actions. The cloud deployment model is expected to exhibit a higher adoption compared to the on-premises deployment model. Cloud-based solutions are gaining a firm hold on the market, due to growing demands for improved service and cost-effectiveness, and the increasing needs of organizations to keep track of operational processes for maintaining productivity. The manufacturing industry vertical is expected to have the largest market share and lead the market during the forecast period. IoT Analytics can be exploited by manufacturers to create smarter products; connect and integrate with customers; streamline innovations, planning, and pre-manufacturing processes; and improve post-manufacturing support and services. 

COMPETITIVE LEADERSHIP MAPPING TERMINOLOGY

The vendors have been placed into 4 categories, based on their performance in each criterion: “visionary leaders,” “innovators,” “emerging companies,” and “dynamic differentiators.” The top 25 players have been evaluated in this section of the report. The analysis has been carried out based on specific parameters and scores have been assigned accordingly.

VISIONARY LEADERS

Vendors who fall into this section receive high scores for most of the evaluation criterion. The vendors in this section have a strong and established product portfolio, and a very strong market presence. They provide mature and reputable AoT software and services that cater to a wide range of verticals, globally. They also have strong business strategies. The companies falling in this category include IBM, Microsoft, Oracle, SAP, Cisco Systems, Dell Technologies and Google.

INNOVATORS

The companies falling in the innovators section include PTC, Hitachi, Teradata, Glassbeam, AGT International, Software AG, TIBCO Software, Striim, Ericsson, and Vitria Technology. These players have a strong product portfolio and robust business strategy to achieve continued growth. These players have innovative products and potential to build strong strategies for their business growth to be at par with the visionary leaders.

DYNAMIC Differentiators

The vendors included in the dynamic differentiators section have the potential to broaden their product portfolio to compete with other key market players. The companies falling in this category include HPE, Amazon Web Services and General Electric.

EMERGING COMPANIES

Emerging companies in the AoT market include Greenwave Systems, Splunk, Salesforce.com, Information Builders, mnubo and RapidMiner. These players have the potential to build a strong product portfolio and business strategy to compete in the market with the visionary leaders and innovators.

TOP VENDORS
In Analytics of Things Solutions

  1. IBM Watson Internet of Things (IoT) platform
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    4.0
  2. MICROSOFT Azure Internet of Things (IoT)
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    3.9
  3. SAP Cloud Platform Internet of Things
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    3.6

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KEY BUYING CRITERIA

Product Maturity
Strategic Maturity
Use Case Maturity
Most IMPORTANT
4.2
4.2
3.8
Product Features and Functionality
4.50
4.00
4.40
Breadth and Depth of Product Offerings
3.60
3.55
3.95
Delivery
5.00
4.85
3.85
Business Applications
4.55
4.80
3.35
Support and Services
3.25
3.50
2.70
LEAST IMPORTANT LESS IMPORTANT

TOP VENDORS

  • Platform is an array of unstructured data formats, including text, image, video, speech, and location.

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  • This service can be used by IoT to process incoming telemetry, detect events, and perform aggregation

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  • Provides various business applications, including SAP fraud management and embedded predictive algorithms through which it can monitor, analyze, and automate business processes in real time.

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  • Oracle IoT cloud offers a highly interactive and user-friendly visual interface, it integrates with Oracle Data Visualization cloud, and Oracle Business Intelligence for visualization, reporting, dash boarding, charts & graphs, and more.

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  • Cisco IoT Analytics Infrastructure encompasses Cisco CSA that helps enterprises to gain the advantages of real-time analytics.

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  • Data scoring and light computing at the edge of the devices minimizes the costs of transporting and saving of data.

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  • Offers predictive modelling and operationalization for numerous different outcomes

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  • platform is capable of providing advanced analytics, AI, simulation tools, data integration, and orchestration of data.

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  • Google provides its IoT analytics through Google Cloud Platform, which provides an efficient, scalable, and affordable solution to its customers.

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  • HPE offers high data visualization for the representation of data in pictorial or graphical format.

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  • GE is at the forefront of converging industrial machines, data, and the internet.

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  • AWS customers are privileged to use AWS IoT with the help of AWS Management Console, Software Development Kits (SDK), and AWS Command Line Interface.

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  • combines text path, machine learning, pattern, graph, and statistics within a single workflow application.

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  • Software AG enhanced its streaming analytics portfolio Apama with the addition of predictive analytics and IoT standards to its platform.

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  • Ericsson provides its analytics of things solution through User & IoT Analytics solutions.

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  • The platform is built to handle all types of data format, which includes structured, semistructured, and unstructured data.

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  • Offers fastest data exploration method that explores data from multiple data sources, which includes spreadsheets, CSV's, SQL, text files, HDFS, and many others.

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  • AGT provides a complete suite of professional services, especially for oil & gas customers to fulfill the operational requirements of the customer.

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  • Offers real-time event processing that is capable of turning data sources into realtime actions.

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  • Offers data processing techniques for both data in motion (real-time streaming data) as well as on historic data collection.

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  • Offers time-series analytics that enables trend analysis and pattern detection.

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  • Platform facilitates easy streaming data pipelines, which includes Change Data Capture (CDC), which is useful for real-time log correlation, streaming analytics, and edge processing & cloud integration.

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  • Offers self-diagnosis and self-healing systems that are instrumental in minimizing support costs.

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  • Offers iWay Big Data Integrator that is instrumental in cleaning, enriching, and managing the data.

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  • Processes more than 250 machine leaning models in data-cluster, paving the way for deploying the predictive analytics in Hadoop.

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  • AWS customers are privileged to use AWS IoT with the help of AWS Management Console, Software Development Kits (SDK), and AWS Command Line Interface.

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