What is IoT Analytics Software

IoT is a combination of technologies, software and services, tools, policies, platforms, guidelines approaches, and a set of professional services. IoT Analytics 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 data-driven prediction analytics, as well as, optimization and simulation on the collected data, to generate useful information.

360Quadrants recognizes the below-listed companies as the best IoT Analytics Software -

Top 10 IoT Analytics Software in 2020:

  1. IBM
  2. MICROSOFT
  3. SAP
  4. ORACLE
  5. CISCO
  6. DELL
  7. HITACHI
  8. HPE
  9. PTC INC
  10. GOOGLE

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 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.

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.

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.

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.

Best IoT Analytics Software 2022

Comparing 27 vendors in IoT Analytics Software across 237 criteria.
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Popular Comparisons
4
IBM offers IBM Watson and IBM Bluemix solutions under its IoT Analytics Software. Organizations can make use of Watson IoT, which uses the Bluemix platform to analyze IoT data. Bluemix platform takes data from sensors and sensor-enabled devices and performs analytics on it. The platform makes use of Complex Event Processing (CEP) to analyze real-time streaming data for generating and determining patterns and create insights using business indexes and data streams. Watson AoT processes structured and unstructured data obtained from flat files, in-database, data warehouse, Hadoop, and spreadsheets (IBM SPSS Statistics, Excel files, CSV files, and SAS files). IBM also offers readymade IoT solutions enabling organizations implement it quickly.
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3.9
Microsoft offers IoT analytics software through its Azure IoT Suite and Stream Analytics, which are used in various business areas, including banking, financial services, retail, education, healthcare, and marketing sectors. Any device, regardless of the IoT device type or OS can be connected to the Microsoft Azure IoT suite and the cloud, where they can be used to communicate between employees and customers. Microsoft also provides Business Intelligence (BI) tools to gain deeper insights into what employees and customers need, by analyzing the IoT data.
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3.6
SAP offers IoT analytics software through the SAP HANA Cloud platform. SAP HANA is being widely accepted by various industry verticals as it can be integrated not only with the social media module in custom Customer Relationship Management (CRM) but also with R and Hadoop to store, pre-process, analyze, and compute data in real-time analysis. The platform helps analyze data from machines, streaming events, and business operations and allows frontline workers to make use of real-time analytics to maintain productivity.
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3.5

Oracle provides an IoT platform to develop new IoT services quickly, using Oracle portfolio of products. This enables organizations to handle growing volumes of data, streamline application development and deployment, automate integration of data, and protect the data across the entire IoT value chain. Oracle provides a variety of IoT analytics solutions, including Oracle IoT Cloud Platform as a Service (PaaS) and Oracle IoT applications with built-in analytics for Key Performance Indicators (KPIs), anomaly detection, comparative analytics, and predictive analytics. Oracle also provides an IoT cloud service which is a secure and scalable platform to quickly build and deploy IoT applications, and capture and analyze IoT data.

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3.3
Cisco offers IoT analytics software such as Connected Streaming Analytics (CSA) platform, Cisco IOx APIs, Cisco Fog Data Services, and Cisco Edge Analytics Fabric as a part of its AoT offerings. The Cisco CSA offers predictive, actionable insights, which are collected through high-velocity streams of live data generated from numerous sources, such as sensors and from the edge of the devices, to facilitate real-time governance and by which immediate actions can be taken. Cisco CSA for IoT caters to various industry verticals including retail, IT, network deployment, mobility, and contact centers. In retail, customers can track in-store patterns and study consumer’s shopping patterns and buying behavior so that they are well equipped with the inventory and can also enhance the user's experience. Cisco Edge Analytics Fabric provides flexibility to the enterprises to collect, process, and analyze the data from where it is generated at the edge of the devices.
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3.2
Dell Technologies, Inc. is one of the prominent players in IoT analytics software marketplace. The American multinational specializes in digital transformation, IT transformation, security transformation, and workforce transformation. Dell’s enterprise solution includes servers, networking, storage, mobility, and desktop products. Dell provides IoT analytics infrastructure that encompasses Dell IoT platform and similar software, such as edge analytics and Dell Statistica predictive analytics software.
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3
Hitachi offers Lumada as its core IoT platform. This open source platform enables technologies from Hitachi IoT partner system to integrate and provide numerous solutions for a variety of industrial applications. The company offers various services in the areas of cloud, big data analytics, infrastructure, data protection, and application services. Moreover, it offers software solutions such as Hitachi Content Intelligence, Hitachi Streaming Data Platform, Pentaho Data Integration and Analytics, which can be integrated into Lumada IoT platform.
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3
HPE provides Vertica Analytics Platform and Universal IoT Platform as its AoT offerings. The platforms offer data visualization for representation of data in pictorial or graphical format and offer in-memory analytics for faster data processing. The platforms are powered with data engines which process thousands of rows, utilizing the full system, for achieving fast query processing. They support a variety of data sources, such as Excel spreadsheets, flat files, and Hadoop.
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3
The company offers an array of software solutions, such as Computer-Aided Design (VCAD) modelling, Service Lifecycle Management (SLM), and Product Lifecycle Management (PLM). The company also offers IoT solutions to enable customers to connect smart things, manage and analyze data, and develop applications. PTC offers IoT analytics solutions under its ThingWorx solution, a technology platform which enables customers to create and deploy applications and solutions. The solution also includes cloud-based tools which facilitate users to connect products and devices to the cloud, process, transform, store, and organize product and sensor data. The on-premises and on cloud deployment models provide the customers with an option to choose the delivery model. This has strengthened PTC’s customer base.
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3
Google provides its AoT solution through Google Cloud IoT Core. Google’s global clientele base is spread across various industries, such as automotive, banking, consumer goods, education, energy, engineering, entertainment, environmental, financial services, food, beverage, government, healthcare, insurance, manufacturing, media, retail, technology, telecommunications, transportation, and travel & hospitality. Google Cloud IoT Core offers analytics solutions to enterprises. The company is striving to expand its portfolio with new technological developments. To accomplish this, Google has invested a significant share (15% during the last 3 years) of its revenue on R&D activities.
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2.8
AWS IoT analytics solutions helps users to connect devices to cloud and each other through device gateways and AoT device SDK. AWS IoT Analytics enables the users to constantly ingest, filter, process, and route streaming data coming from connected devices. The solution enables the users to configure the data in usage with other devices using AWS Lambda, Amazon Kinesis, DynamoDB, Amazon Elasticsearch Service, and Amazon Machine Learning.
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2.8
Teradata has specialized itself as a leading provider of software solutions and services. Its major offerings include Teradata Database Software, Teradata Workload-Specific Platforms, Teradata Aster Analytics Discovery Platform, Teradata QueryGrid, Teradata Marketing Applications. Apart from software solutions, the company offers Teradata Technology and Implementation services, Teradata Cloud Services, Teradata Managed Services, and customer support and training services.
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2.8
GE is at the forefront of converging industrial machines, data, and the internet.The company is putting sensors on jet engines, gas turbines, and other connected devices and connecting it to the internet to analyze the data and gather significant insights from the data. GE provides advisory, education, implementation, and managed services as a part of its service offerings. The company provides Predix platform with a set of rich features that include: Predictive intelligence – provides digital twin technology that forecasts the lifespan of an asset based on machine learning. Provides edge to cloud capabilities that are sending only the relevant data to the cloud to gain significant insights. The software provides scalability of ingesting, processing, and analyzing multi-terabytes streams from millions of assets.
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2.7

The Cumulocity IoT from Software AG is an IoT platform which connects any device from any of the cloud platforms and can be integrated with any of the applications. The platform is very quick to start, in just ten minutes and in very simple steps. The platform offers the benefit of not requiring coding and analysis for business users and analysis can be carried out without coding or programming skills. Users require the same APIs, data and analytics models everywhere, in the cloud and on-premises.

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2.6
Glassbeam offers a platform that helps users in building analytics from Log data in a single step. The platform makes use of Semiotic Parsing Language (SPL)which is a single-step solution to transform machine logs of any format and device into a machine data analytics app. The company offers SCALAR platform which is a fully scalable, parallel, asynchronous, machine data analytics platform that transforms any log format into actionable information. The platform adjusts itself to optimize the system while ensuring efficient resource utilisation. The company has developed Rules Engine which is a highly scalable event processor, which enables users to develop complex rules on their incoming streams or batched data.
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2.5
Ericsson provides its analytics of things solution through User & IoT Analytics solutions. The company’s solution provides real-time analytics, massive data analysis, database performance, and protects the user’s privacy. Ericsson's IoT Accelerator offers global connectivity and device management in on a single platform. It reduces the time to market, lowers the risk of investment, and almost eliminates the complexity for IoT applications and services. Ericsson's Smart manufacturing offers a simple, secure and stable connectivity in side the factories. The company's Device Analytics solution enables users to measure their wireless connectivity performance from mobile devices of any kind and sort.
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2.4
Tibco IOT Analytics solution gathers data from sensors, combines it, runs logic, and connects to the user's cloud services. It allows the user's edge devices to execute app logic independent of their core systems. Tibco's predictive analytics and modeling tools facilitate users to gain insights on Internet of Things data so that they can act in real time. The solution simplifies connectivity with a flow-based, web UI for building integration applications for Internet of Things edge devices. Project Flogo is the lightest IOT connectivity framework that offers a host of connectity features.
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2.3
AGT offers IoT analytics as its predictive analytics offering based on the cloud deployment option. The platform allows an entire new generation of vertical IoT applications that will drive enhanced business processes, resulting in improved value and new revenue streams. The platform also resolves key issues in IoT analytics, data management and visualization, employing solutions that have been tailor made for each application. Also, the platform integrates easily with existing sensors, network infrastructure and end-user applications.
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2.3
Salesforce offers Einstein Analytics platform and IoT Cloud both of which have been powered by Thunder Wave Analytics. Einstein analytics platform integrates AI to the analytics workflow, enabling users to automatically create CRM insights. The platform's AI-augmented analytics provide insights about the past, while it also helps businesses in making future decisions. The AI helps optimize marketing campaigns, by recommending actions which improve customer service and boost sales. The platform also comprises specific role based KPIs, giving users access to the newest data from any IoT device. The platform is built on a secure and scalable platform and it offers seamless upgrades to ensure that the technology stays up to date.
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2.3
Splunk Enterprise ingests data from applications, sensors, devices, and so on. Post setting up the data sources, Splunk Enterprise indexes the data stream and resolves it into a series of individual events and metrics that the users can view and search. Splunk IAI is an application that the users can use to track asset health, notify on metric anomalies, design custom metrics, conduct root cause analysis for issues across data sources, and measure entire equipment effectiveness in real time. Splunk IoT Platform Data also helps in reducing downtime of critical assets.
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2.1
Vitira's platforms offer enhanced customer experience by deliverng a resilient and predictable infrastructure for service delivery that reduces churn and cost of managing increasingly complex environments. The platforms easily manage streaming or batch data from disparate devices and help users in deploying ML and augmented intelligence using VIAs drag and drop libraries. Also, they automate processes and workflows like anomaly detection, incident lifecycle automation, dynamic change management, dynamic failure prediction.
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2.1
Striim’s patented software collaborates real-time data collection, stream processing, pipeline monitoring, and real-time delivery with validation in a single product. It continuously collects a wide variety of high-volume, high-velocity data from organization's databases , log files, messaging systems and IoT devices in real time. The platform also integrates rapidly with existing data management and ML solutions to operationalize earlier defined models via stream processing. The platform is robust, sclaable, secure and reliable.
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2
Greenwave Systems, Inc. is an IoT and machine-to-machine company delivering comprehensive software and services to network architects and service providers to address the interoperability, flexibility, security, and scalability in a single unified IoT solution. The company specializes in offering IoT solutions, managed services, enterprise solutions, network services, home energy management, connected LED lighting solutions, and others.
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1.8
Information Builders' WebFOCUS possesses an interactive user interface, which provides visually intuitive and highly efficient workflows. It also incorporates UI/UX best practices throughout. The solution enables users and administrators to rapidly create dashboards that combine content from multiple data sources and formats. The solution also provides users with full-featured report writing and casting capabilities which facilitate self-service, enterprise, financial, or managed reporting. The company's API management technology allows users to reuse existing application and infrastructure investments for web-oriented and event-driven architecture.
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1.7
Mnubo is specialized in offering IoT analytics for service providers, enterprises, and device manufacturers. mnubo’s solution empowers manufacturers to improve product usage, enhance customer engagement, and lower customer churns with insights generated from data collected from IoT devices. The company’s SmartObject allows exploration and analysis of sensors data and events to gather insightful information about connected devices.
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1.4
RapidMiner has been seamlessly integrated and enhanced for developing ML models. It helps organizations in designing models with the help of a visual workflow designer or automated modeling. The platform collaborates multiple datasets together and creates new columns using a simple expression editor. It automatically creates new features from data to enhance model accuracy. The platform also allows organizations to execute data prep and ETL inside databases to keep their data optimized for advanced analytics.
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The Alteryx platform helps analysts to change the way they discover, prioritize, and analyze data throughout their organizations. The data management, cataloging, and collaboration software offered by Alteryx accelerates end-to-end analytic process to dramatically improve productivity and information governance, resulting in better business decisions and quicker turnaround times.
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Top IoT Analytics Software
-- by Shambhavi Gajul
Frequently Asked Questions (FAQs)
The IoT analytics market size is expected to grow from USD 7.2 billion in 2017 to USD 27.8 billion by 2022, at a Compound Annual Growth Rate (CAGR) of 31.0% during the forecast period. Factors such as the tremendous growth of IoT data is expected to fuel the market growth. However, the ownership and control of IoT data is expected to restrain the market growth.
The IoT analytics solution and service vendors have implemented various types of organic as well as inorganic growth strategies, such as new product launches, product upgradations, partnerships and agreements, business expansions, and mergers and acquisitions, to strengthen their offerings in the market. The Major players operating in the market include IBM Corporation (US), Microsoft Corporation (US), Oracle Corporation (US), SAP SE (Germany), Cisco Systems, Inc., (US), Dell Technologies, Inc. (US), Google, Inc. (US), Amazon Web Services, Inc. (US), HP Enterprise Co (US), PTC, Inc. (US), Hitachi, Ltd. (Japan), Teradata Corporation (US), Salesforce.com, Inc. (US), Greenwave Systems, Inc. (US), and mnubo, inc. (US).
Predictive analytics transforms data into valuable insights, facilitating enterprises to optimize business processes, enhance process efficiencies, and increase customer satisfaction. Predictive analytics makes use of real-time data as well as historic data to come up with futuristic outcomes before the actual event takes place. The predictive analytics type is expected to have the largest share in the AoT market due to its ability to determine data and predict future outcomes and trends. The predictions that flow from predictive analytics are transformed into a set of recommended actions that will generate business value. This assists procurement professionals to view business scenario and build future operational strategies. Predictive analytics can also be used for demand forecasting using multiple regression models, which helps organizations determine demand and supply forecasts for different product categories. Such forecasts can prove beneficial while calculating the company revenue and budget growth. Companies are also focusing on providing predictive maintenance and asset maintenance using predictive analytics to understand the device repairing time, minimize downtime, and take swift corrective actions. Predictive analytics when incorporated in AoT, assists a manufacturing unit to ensure continuous operations by implementing asset maintenance or helps a government institute to shut down their servers if suspicious web traffic is detected.
The top 10 use cases in IoT Analytics market are: Predictive maintenance, Quality inspection & assurance, Manufacturing process optimization, Supply chain optimization, AI-driven cybersecurity & privacy, Automated physical security, Automated data management, Smart assistants, AI-driven research & development, Autonomous resource exploration.
The IoT Analytics Market is moving towards the cloud based environment. Cloud-based solutions require less physical set-up, incur lower maintenance costs, and provide 24/7 accessibility from anytime, anywhere. Cloud-based solutions prove to be flexible, agile, and cost-effective, as compared to on-premises solutions. Cloud-based AoT helps organizations to reduce cost and IT complexity; it also improves business agility and increases collaborations by shared services. Globally, large enterprise and SMEs are shifting toward cloud-based solutions to streamline their processes easily and minimize upfront costs. Some of the prominent vendors offering cloud-based AoT software and services include IBM Corporation, Oracle Corp., AWS, and Salesforce.com, Inc.
In February 2019, IBM announced access to its IBM Watson on any cloud. Also, the vendor can deploy AI software to automate business wherever the data resides. In June 2019, Cisco announced software innovations for simplified management and security of networks. Also, it introduced new artificial intelligence and machine learning capabilities that enable IT teams to function at machine speed and scale through tailored network insights.
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