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12 Real-World Solutions for IoT Analytics

• February 26, 2016

The Internet of Things -- a network of connected devices that can send and receive data over the Internet -- is a hot market topic. Analysts predict there will be tens of billions of these devices by 2020. They’ll be in your home and in your office buildings; you’ll be wearing them for your health and wellness. They will be in your cars, in factories, and on farms.

These devices are generating a lot of data. On the business front, organizations can use analytics from IoT data to help drive efficiencies as well as increase revenue. IoT analytics will help drive new business models, too. For example, energy companies are using IoT analytics for preventive maintenance to determine when a part will fail. Organizations are using IoT for asset management. Retailers are using IoT and beacon technology to offer marketing promotions to customers when they are in a store. The list goes on.

TDWI research indicates that slightly less than 20 percent of organizations we survey are using IoT and/or machine data today for analytics, and that number is set to double in the next few years if users stick to their plans.

Of course, collecting IoT data by itself is not a path to value. Data must be analyzed and acted upon to drive real benefit. What software vendors today can support IoT analytics? To help those starting on their journey, I compiled this list of real-world solutions for IoT analytics. To make the list, the company needed to meet the following criteria:

• IoT analytics is a strategic focus (e.g., it is on the company website, in blogs, etc.)

• The vendor possesses analytics software today that can actually analyze IoT data (i.e., there are named products and/or platforms; the product is currently shipping, not in beta)

• The company’s solutions are in production at customer sites and the company can provide a customer references/use cases demonstrating current use.

• The vendor is not a service provider selling a niche solution (e.g., smart pill bottles).

The second criterion is especially important. I’m concentrating on vendors that are providing software and platforms for IoT analytics. This list is not about the IoT network infrastructure or IoT devices. Yes, all of this is needed for an IoT deployment and there are many great vendors supplying this infrastructure. Instead, I’m focusing on analyzing the data coming from IoT.

I had the opportunity to speak to a dozen vendors that fit the bill. I asked the questions; they provided the answers. The vendors are presented in alphabetical order. I will continue to add vendors to the list as they meet these criteria and/or I receive their input, so you may want to periodically revisit this list to see if a new vendor was added.

Jump to: 

Datameer     Dell     Glassbeam     IBM     Oracle     Pentaho

SAS     Space-Time Insight     Striim     Teradata     TIBCO     Vitria

 

Datameer

Datameer provides a big data analytics solution native for Hadoop that includes pre-built functions that are delivered via a GUI interface to analyze data. The company recently announced a $40 million Series E round of funding led by ST Telemedia, an investment firm based in Singapore, bringing the total funds raised to over $76 million. The company will use this money to continue to grow its business.

I spoke with Andrew Brust, director of market strategy and intelligence, about IoT.

Upside: What is your company’s IoT vision?

Andrew Brust: Datameer’s mission is to make big data analytics simple so that analysts and business users can more easily analyze big data. We view the IoT as an incredible opportunity for organizations to analyze large volumes of sensor and device data to improve customer service and dramatically lower operational costs, and we have customers doing that today.

What are your products and platforms that support IoT analytics?

Datameer combines data integration, preparation, analysis, and visualization into a single application that helps business analysts turn massive volumes of machine-generated sensor data into valuable, timely insights.

What is unique about your products or platforms?

Datameer is the only big data analytics solution built natively on Hadoop and optimized for the evolving big data ecosystem. That means there’s no need to duplicate data or move it out of Hadoop to analyze it. Datameer is also unique as an end-to-end solution, from integration through visualization, and uses a “schema-on-read” approach so that new use cases and applications can be logically modeled on the same dataset without any replication or changes to the physical schema.

What are one or two use cases where your products or solutions are used today?

Vivint, the largest home automation company in North America, is leading the charge in the data-driven, connected home movement. Serving more than 800,000 homes, Vivint’s touchscreen panel, the hub through which all of their other products communicate, creates a streamlined network that connects all of the home’s smart systems, including security, HVAC, lighting, small appliances, video, and other devices.

Datameer is used to join and analyze terabytes worth of data collected from its Internet of Things solution and various in-home automation, security, and energy management devices (such as thermostats, smoke alarms, automatic locks, and door and window sensors) to better understand usage patterns and improve services. In particular, Datameer can integrate and analyze not just row data but also streaming data, which is a key component to its smart home analytics solution. Finally, it was important to Vivint that Datameer seamlessly integrated with its Hadoop platform (rather than a solution that was just retrofitted to work with Hadoop) so their employees could be more efficient and work seamlessly with Hadoop.

Another example is a major global telecommunications service provider that wants to optimize its network capacity to meet growing voice and data demand. Management’s goal was to have enough capacity to meet existing and forecasted demand, but not excess capacity, which would inflate capital expenditures. Decision makers use Datameer to generate network traffic “heat maps” from subscriber, network, and location data, which helps them visualize highly congested network areas and areas with excess network capacity. Now they can see where demand is very near to capacity -- and thus where LTE rollouts should be prioritized and marketing efforts should be scaled back. Conversely, they can also identify geographic areas where excess capacity exists and marketing activities should be ramped up.

Where can readers find more information?

Readers can visit www.datameer.com.

Jump to: 

Dell     Glassbeam     IBM     Oracle     Pentaho

SAS     Space-Time Insight     Striim     Teradata     TIBCO     Vitria

 

Dell IoT Analytics

Dell, with its acquisition of Statistica and the recent introduction of its Edge Gateway that sits at the edge of the network (near devices and sensors) and includes local analytics, has both hardware and analytics in its IoT portfolio. In January 2016, Dell opened its third IoT lab in Singapore in collaboration with Intel. Its two other IoT labs are in Silicon Valley and Limerick, Ireland. I spoke with John Thompson, general manager of advanced analytics at Dell.

Upside: What is your company’s IoT vision?

John Thompson: Dell takes a pragmatic approach to the Internet of Things by combining a community of technology providers and domain experts with our broad portfolio of solution-enabling assets. Dell’s approach allows you to architect for analytics, put security first, and start with what you have.

What are your products and platforms that support IoT analytics?

Dell offers a comprehensive portfolio of products to support IoT analytics which includes Infrastructure, analytics, security, IoT services, and software. These include:

• Infrastructure: In addition to traditional endpoints, servers, and cloud and data center storage, Dell has a purpose-built intelligent edge gateway that supports analytics at the edge of the network.


• Analytics: Through a combination of Dell Boomi, Dell Statistica, various partner middleware, and the Edge Gateway, Dell offers an agnostic platform that allows you to embed analytics everywhere in the distributed network.


• Security: Dell Network Security, Security Services, Identity and Access Management, and GRC (Governance, Risk, and Compliance) allow you to protect your enterprise and infrastructure from the data center to the cloud and everything in between. The Dell Edge Gateway also provides hardware-level security, such as root of trust and BIOS-level control.


• IOT Services: These allow organizations to take a pragmatic approach to IoT strategy and deployment, bringing vertical and use-case experience to the project.


• Software: Cloud Client Manager for IoT gateways, Statistica, SecureWorks, Boomi and other software offerings support security and manageability for IoT projects.

What is unique about your products or platforms?

The Dell difference includes a broad portfolio of hardware, software, and services, along with a rich partner ecosystem and deep domain expertise. Additionally, along with Dell Boomi and Statistica, Dell can deliver analytics payloads via its Native Distributed Analytics Architecture to any endpoint, device, or gateway, anywhere in the world. We provide security solutions and expertise and expanded I/O via connections to legacy and modern devices, systems, and endpoints via the Edge Gateways. Middleware can aggregate, normalize, and analyze the data, no matter what the protocol, from traditional industry to new approaches such as ZigBee and CAN bus. Our solutions build on the Dell heritage of reliable quality processes, and global hardware and services support.

Can you provide one or two use cases where your products or solutions are used today?

Dell has several industry-specific blueprints that span building automation and smarter cities, industrial controls and manufacturing, fleet management and logistics, and healthcare and telemedicine. For example, one of our clients, ELM Energy, monitors and manages power for worksites such as mines and data centers. It uses the Dell Edge Gateway to manage power sources in real time so that the most efficient source can be utilized while never losing power. The analytics are performed at the edge of the network. Additionally, ELM Energy offloads this data to the cloud to perform advanced analytics for use cases such as maintenance determination.

Some of our other IoT clients include Chitale Dairy, KMC Controls, JTG Racing, and Fujiian University.

Where can readers find more information?

Readers can visit:

http://www.dell.com/IoT

The Dell IoT Framework: http://i.dell.com/sites/doccontent/corporate/secure/en/Documents/Iot-infographic-refresh.pdf

http://www.dell.com/en-us/work/learn/internet-of-things-industries

Jump to: 

Datameer     Glassbeam     IBM     Oracle     Pentaho

SAS     Space-Time Insight     Striim     Teradata     TIBCO     Vitria

 

Glassbeam

Glassbeam was founded in 2009 to help product companies make sense of complex data from connected devices (even before the phrase “Internet of Things” became popular). Its customers are primarily manufacturing and OEM providers with large volumes of complex data. Glassbeam’s core platform is cloud based. However, recently the company decided to move to the edge of the network to support analytics in distributed devices in real time. I spoke with Puneet Pandit, founder and CEO of Glassbeam.

Upside: What is your company’s IoT vision?

Puneet Pandit: Glassbeam was founded with the mission to help companies make sense out of complex machine data collected from connected devices. Our value proposition is to take any kind of machine data format (unstructured, semi-structured) and turn it into structured data that can be analyzed.

What are your products and platforms that support IoT analytics?

Our core platform is Glassbeam Scalar; it performs assimilation, aggregation, and transformation of data. The platform runs as a service in the cloud. We provide value through front-end applications. Glassbeam Edge will reside in close physical proximity to actual devices. It will provide all the benefits of real time analytics on data streams.

Analytics are provided through application modules. These include:

• Glassbeam Log Vault, a log management application that lets users access and search device logs


• Glassbeam Explorer, an application to help users explore raw logs through faceted search


• Glassbeam Workbench, an application that provides descriptive and predictive analytics. It includes a drag and drop visual analysis interface; Workbench also includes trend analysis, regression, and correlation


• Glassbeam Rules and Alerts, an application that allows customers to define business and operational rules and alerts for operational monitoring and intelligence.


• Custom applications, a professional service offering that helps create custom applications to provide insights on parsed machine data.

What is unique about your products or platforms?

Our biggest differentiator is the ability to ingest complex machine data (including XML and SNMP), parse it, and put it into a structured format. In the world of IoT, there is no standardization on data formats. Our engine can ingest any log and parse it into structured format.

What are one or two use cases where your products or solutions are used today?

Two great use cases are in asset management (including asset tracking, asset maintenance, and asset recovery) and preventive maintenance. For example, a company like Vytronus (a medical device manufacturer) uses Glassbeam to help collect and analyze data to understand device performance. Gridscape uses Glassbeam in its smart grid solutions for monitoring vehicle electrical charging stations.

Where can readers find more information?

Readers can visit: http://www.glassbeam.com

http://www.glassbeam.com/glassbeam-glance/

http://info.glassbeam.com/gbthingworx

Jump to: 

Datameer     Dell     IBM     Oracle     Pentaho

SAS     Space-Time Insight     Striim     Teradata     TIBCO     Vitria

 

IBM

From its vision of a smarter planet more than five years ago to the company’s recent opening of its global headquarters for Watson IoT in Munich, Germany, IBM is heavily committed to the Internet of Things. In March 2015, the company announced its intention to invest more than $3 billion to address the needs of clients looking to capitalize on the increasing instrumentation and interconnectedness of the world driven by the IoT. IBM recently rebranded its IoT products to Watson IoT to signify the coming together of cognitive computing and IoT capabilities -- a clear indication of IBM’s commitment to IoT analytics. I spoke to Neil Postlethwaite, director, Watson IoT Platform at IBM to understand more about IBM IoT.

Upside: What is IBM’s IoT analytics vision?

Neil Postlethwaite: IoT goes beyond connected things; it is driving a digital disruption into the physical world. Watson, with its unique abilities to sense, reason, and learn, can generate new insights from IoT data to the benefit of both business and society alike. These cognitive IoT analytic capabilities can improve operations, help create new transformational business models, and drive improved customer engagement by uncovering and learning patterns in the vast sea of data. IBM believes cognitive IoT will reshape the future of business.

What products and/or platforms support IoT analytics?

IBM’s IoT platform is called The IBM Watson IoT Platform -- a set of capabilities that can learn from, and infuse intelligence into, the physical world. It is available in multiple form factors -- public cloud, dedicated space on public cloud, and local in customer data centers -- in all cases fully managed.

The platform consists of four parts:

• Watson IoT Connect is used to securely attach and manage IoT devices.


• Watson IoT Information Management is used to transform, store, archive, and integrate data from IoT devices. Watson IoT Information Management can pull in data from other sources and platforms, such as weather data sourced from IBM’s recent acquisition of the Weather Company's technology assets.


• Watson IoT Analytics is IBM’s predictive, cognitive, real-time, and other analytics offered as a set of services that can be composed and brought together to provide insight on the data arriving in the platform.


• Watson IoT Risk Management provides management of IoT landscapes and business resiliency functions such as anomaly detection.

The Watson IoT Platform forms part of the IBM Bluemix cloud platform for application development and delivery.

What is unique about IBM’s products and platforms?

We believe there are a number of differentiators for our IoT offerings. These include:

• Making cognitive analytics capabilities accessible to all developers and engineers via analytics as service including industry specific models [see below]
• IBM’s ability to partner to bring in new kinds of data applicable to all IoT use cases to its platform
• Our ability to deliver complex cloud infrastructure to our clients and provide capabilities in individual geographies and environments dedicated to individual clients (necessary for many IoT use cases)

How are your solutions being used today?

IBM offers IoT solutions in areas including asset management, facilities management, continuous engineering, automotive and electronics in addition to its Watson IoT Platform. For instance, manufacturing, utility, and other industries use IBM IoT solutions to perform preventive maintenance for equipment. Automotive companies are using IBM IoT to help deliver smarter connected vehicles. Industrial companies are using IBM IoT to track assets, better understand how they are operating, and improve operational efficiency.

Which customers are currently using your IoT products?

IBM has over 3000 customers spanning multiple industry verticals using its IoT solutions, including Whirlpool (consumer products), Tyréns AB (engineering and construction, Daimler Car2go (new services division of auto manufacturer), and KONE (industrial).

Where can readers find more information?

Readers can visit www.ibm.com/iot

Jump to: 

Datameer     Dell     Glassbeam     Oracle     Pentaho

SAS     Space-Time Insight     Striim     Teradata     TIBCO     Vitria

 

Oracle IoT Cloud Service

Enterprise software and hardware provider Oracle is pushing strongly into the cloud. Its strategy is to bring Oracle’s applications, software, technology and middleware to “anyone, anywhere via an Internet browser or mobile device.” This strategy extends to IoT as well. I heard from Eric Rogge, director, competitive intelligence, Oracle Corp about how the Oracle Cloud enables IoT.

Upside: What is your company’s IoT vision?

Eric Rogge: With Oracle’s IoT Cloud Service, a broad portfolio of cloud services and market leading enterprise apps, enterprises can now integrate physical devices and business data. This integration of physical and non-physical data can grow current business value and reveal promising new business models.

What are your products or platforms that support IoT analytics?

Available products and platforms include:

• Oracle IoT Cloud Service is used to connect to and manage IoT devices. Oracle IoT Cloud Services allow users to securely gather, store, transform, visualize, and publish massive amounts of data and analytics from IoT devices.


• Oracle Business Intelligence Cloud Service enables users to integrate, store, transform, discover, and visualize IoT and other enterprise data. It is mobile enabled.


• Oracle Big Data Cloud Service enables users with Hadoop clusters with Spark and Oracle R Advanced Analytics to analyze big data. They can combine IoT device stream, external, and enterprise data using descriptive and predictive analytics.


• Oracle Mobile Cloud Service is used to rapidly develop and use native and hybrid mobile IoT analytics and control applications.

What is unique about your products/platforms?

Oracle IoT Cloud Service is an integrated, secure, scalable platform for rapidly launching IoT solutions. It easily connects to Oracle’s proven enterprise applications and the broadest portfolio of IaaS, PaaS, and SaaS services available.

Can you provide one or two use cases where your products or solutions are used today?

All IoT reference customer names are confidential to Oracle at this time. However, I can give you a few anonymous examples of how our customers are using IoT analytics.

A global industrial equipment manufacturer that manufactures valves, automation components, and other products for process manufacturing industry wants to increase lifetime and reliability of components used in safety and health-critical chemical processes. They use Oracle IoT Cloud Service for real-time filtering and processing of status events from equipment deployed worldwide. This operational data is integrated with their service ticket CRM system to proactively maintain equipment and to advance new model design.

A fleet management services provider serves worldwide transportation fleet operators. Built on Oracle IoT Cloud service, their application provides multiple services including predictive maintenance alerts and diagnostics, insurance-related operations metrics, and fleet operations optimization.

Where can readers find more information?

Readers can visit www.oracle.com/solutions/internet-of-things/index.html

Jump to: 

Datameer     Dell     Glassbeam     IBM     Pentaho

SAS     Space-Time Insight     Striim     Teradata     TIBCO     Vitria

 

Pentaho -- A Hitachi Group Company

Pentaho was acquired by Hitachi in 2015. Throughout its 100-plus year history, Hitachi has been developing what it terms the social infrastructure for modern life. Through its social innovation business, Hitachi is hoping to make the world a better place via smarter cities, cleaner water, and healthier people.

As part of the Hitachi Social Innovation strategy, HDS is actively engaged in the practical use of connected machines and sensors and how the Internet of Things can improve business and society -- what it calls the Internet of Things that matter. The acquisition of Pentaho -- a big data analytics and data integration company -- is a key component of this strategy and has given Pentaho direct entry into the emerging IoT market.

Pentaho will help Hitachi drive innovations that integrate machine data, information technology and analytics. I spoke with Chuck Yarbrough, VP of product marketing at Pentaho.

Upside: What is your company’s IoT analytics vision?

Chuck Yarborough: Big data and the Internet of Things are disrupting entire markets, with machine data merging the virtual world with the physical world. Pentaho is helping those customers that have embraced big data -- including some of the most innovative companies in the industry -- take advantage of the technological disruption that is connecting people, data, and things in order to reshape sectors of the economy.

What are your products and platforms that support IoT analytics?

Pentaho is a key enabler to a broader IoT solution. Pentaho focuses on solutions for managing and automating the entire data analytics pipeline. A big part of this is Pentaho Data Integration (PDI) which processes big data, blends and transforms it, and then delivers it to open-source analytics tools such as R and Weka (Pentaho owns the rights to Weka). PDI is used to prepare the data for advanced algorithms. Analytics can then be embedded into applications.

For the platform as a whole, Pentaho Business Analytics is an enterprise-grade platform that allows customers to integrate and orchestrate machine-generated big data to deliver analytics embedded at the point of impact.

What is unique about your products or platforms?

Our main differentiators include ease of use in terms of simplicity of connecting to a variety of data sources and operating at scale to process vast amounts of data. For IoT data, for instance, we can capture data in motion as it arrives and can then blend it with other data sources and land it in Hadoop. PDI is for big data integration and for high-performance orchestrated ingest. For example, one of our clients monitors every transaction in the stock market. Its data lake is 7 petabytes.

Another key differentiator is that the Pentaho Business Analytics Platform is built on open source. The company’s open source heritage and development model, paired with the strong open source community, is an important resource in keeping Pentaho’s technology current and relevant. The company continues to embrace and engage the open source community to encourage innovative contributions and extensions to its platform.

Additionally, Pentaho offers native integration with technologies such as Hadoop, Spark, Cassandra, or MongoDB, as well as built-in access to R and the offering of an alternative machine-learning solution with Weka.

Can you provide one or two use cases where your products or solutions are used today?

We have a number of customers that have been performing IoT analytics for a while now. For instance, Caterpillar Marine Asset Intelligence embeds Pentaho in their remote monitoring and diagnostic product suite used by customers such as the U.S. Navy or container ships. Pentaho is used to extract, transform, and load streaming data from machine sensors installed on customer equipment. The Weka and R predictive plug-ins with Pentaho help to model and visualize different usage patterns and habits.

With Pentaho, Caterpillar Marine was able to spot a failing generator on a Navy destroyer just before it went on a deployment, identified a problem in a shipping vessel's engine that was leading to fluctuations in fuel usage, and found a faulty fuel injector aboard a supply ship that, once fixed, reduced the ship's fuel consumption by 5 percent and ultimately saved millions of dollars.

Another example is IMS in the insurance space. They are using telematics off of vehicles to determine insurance premiums based on driving data. IMS is using Pentaho Data Integration for streaming data. They pipe the data to their data centers, then transform and enrich it because sensors don’t have a lot of information. Then they analyze it.

Where can readers find more information?

Readers can visit http://www.pentaho.com/internet-of-things-analytics.

Jump to: 

Datameer     Dell     Glassbeam     IBM     Oracle

SAS     Space-Time Insight     Striim     Teradata     TIBCO     Vitria

 

SAS

As a market leader in advanced analytics, SAS has been helping organizations analyze device data before the term IoT became popular. I recently spoke to SAS senior product manager for IoT Saurabh Mishra about SAS IoT analytics.

Upside: What is your company’s IoT vision?

Saurabh Mishra: SAS is going to bring clarity and confidence to the connected world by driving business value from IoT. We do this by integrating analytics with IoT data, where the data is -- at the edge, in motion, or landed. As an important part of this, SAS provides solutions for the complete analytics life cycle for this data, from data capture and integration to analytics and deployment.

What products and platforms do you offer to support IoT analytics?

SAS provides advanced analytics with data mining and predictive analytics; we have offered that for years and it completes the story for landed data from an IoT perspective. However, there are a few products that are core to IoT:

• SAS Event Stream Processing (ESP): ESP is an industry agnostic solution designed to process events or patterns from devices on an industry scale, including millions of points of data with a latency of milliseconds. This could be sensors in manufacturing or data from beacons in a retail store -- whatever the device. Each is collecting more and more data, but unless you can do something meaningful, it is just data. ESP is an embeddable solution. It can be embedded into devices such as gateways.


• Quality Suite: This product is targeted to industries such as manufacturing and the automotive industry. The core capability is around asset performance. It leverages predictive analytics to support scenarios to minimize outages. That can be done today on landed data. Quality Suite can be used in conjunction with ESP for real-time data streams.


• Customer Intelligence Solution: This solution cuts across industries. It combines insights, rules, decisions, and actions into an integrated decision platform for real-time decision making. It can help marketers provide personalized and targeted offerings.

What is unique about your products or platforms?

SAS can work with all kinds of data; streaming data is most relevant when talking about IoT, especially at scale. ESP goes beyond simple analytics. With ESP, an organization can build a model, deploy it into a workflow, score IoT data flowing through a device, and act on it -- even at the edge. It closes the loop. Organizations can deploy models in the stream. However, ESP also allows you to analyze data in the stream itself, using fairly sophisticated algorithms. Our solutions are production ready, mature solutions that have been available for some time without the umbrella of IoT.

Can you provide one or two use cases where your products or solutions are used today?

Here are two. The first is providing a next-best offer based on in-store beacon data. A major large retailer with omnichannel capabilities is using beacons in their stores. ESP is deployed in the store and is collecting data about how a customer is moving in the store. Using ESP together with Customer Intelligence, it is creating a score based on where a customer is in the store and determining which offer is the most relevant. This offer is served up to the customer when s/he is physically at the location.

The other use case is predictive maintenance. A large automobile and truck manufacturer is using ESP in conjunction with Quality Suite to capture data from the sensors on its trucks. It uses predictive analytics to determine whether and when maintenance is needed. If a part failure is imminent, it will provide an alert. If it is not catastrophic, then the maintenance can be accommodated in the next service call.

Where can readers find more information?

Readers can visit www.sas.com/en_us/insights/big-data.html#internet-of-things.

Jump to: 

Datameer     Dell     Glassbeam     IBM     Oracle     Pentaho

Space-Time Insight     Striim     Teradata     TIBCO     Vitria

 

Space-Time Insight

Space-Time Insight is a situational intelligence company that provides visual intelligence for asset-intensive industries. Situational intelligence combines real-time data analysis with traditional situational awareness. For Space-Time, that means changing the visualize-analyze-act from a decision-making point to analyze-visualize-act. The user or system may take the action. IoT is a natural extension of situational intelligence for Space-Time Insight. I spoke to Steve Ehrlich, SVP of marketing and product management at Space-Time Insight.

Upside: What is your company’s IoT vision?

Steve Ehrlich: Our vision for the IoT is for our Situation Intelligence (SI) Suite platform and "SI Intelligence” applications to enable organizations in any industry to realize the maximum benefit from integrating the IoT into their business processes and activities resulting in Space-Time Insight being recognized as a provider of situational intelligence for the IoT. Client benefits include the ability to easily and broadly operationalize insights derived from the IoT to decision makers who can confidently take timely and appropriate action that favorably influences outcomes in response to real-time alerts, analytics-driven recommendations, and actionable at-a-glance visualizations enriched with relevant context.

What are your products or platforms that support IoT analytics?

SI Suite is an integrated platform for developing and running sophisticated situational intelligence applications. It is designed for organizations that want to build their own applications and for any developer building commercial applications for sale. The suite consists of:

• SI Server: Runs applications and interfaces to data sources and analytics models
• SI Viewer: A visual framework for users to interact with data and analysis results
• SI Studio: A development environment for assembling data, analytics, and alarms into situational intelligence applications

Our platform ingests streaming data and performs streaming analytics; therefore, any application created with our development environment to run on our platform benefits from IoT analytics.

What is unique about your products or platforms?

Developers and power users use the development environment within our SI Suite platform to select internal and external data sources including networks of IoT devices for ingestion, correlation, analysis, and visualization. Connection between our situational intelligence server (SI Server) and IoT streams is via the high-throughput, low-latency Kafka message broker connected to a secure, scalable, flexible, and action-oriented IoT management and communications platform.

Analysis includes streaming analytics using Spark Streaming to identify anomalies and events in real time that can trigger alerts, visual alarms, as well as automated responses and other downstream actions. Advanced analytics on all ingested data, including IoT data, is performed across the dimensions of time, geospatial location, and interrelationships to identify and convey insights with drillable details about what happened, when, and where, as well as identify other actual or potentially affected entities. Predictive analytics extends these insights from the past and present to future likelihoods that empower organizations to take appropriate proactive measures.

Data, recommendations, prescribed actions, and other analytics results are conveyed via visualizations as well as via email and SMS alerts. SI Studio also enables developers and unskilled end users to visually and easily tailor the visualizations with drillable details to their specific preferences.

Can you provide one or two use cases where your products or solutions are used today?

One example is a comprehensive real-time, track-and-trace situational intelligence application for mobile assets for the transportation and logistics and construction markets. It tracks the location of mobile assets, including heavy off-road equipment. It can also track and record routes of travel to identify on-road and off-road usage that allows the business to capture tax advantages that are applicable for off-road use of its assets. It monitors the status and health of assets in the field to enable proactive maintenance.

We can also create and track asset groups. Smaller assets tagged with GPS-enabled responders are grouped together with a larger mobile asset (e.g., a truck). All assets within a group should travel as a group. Any asset that is detected as separated from its group and hence possibly left behind, will trigger an alert so it can be retrieved versus recognizing it as lost.

There are other examples, too. In some cases, competitive advantage and corresponding confidentiality with our clients prohibit disclosing references.

Where can readers find more information?

Readers can visit www.spacetimeinsight.com.

Jump to: 

Datameer     Dell     Glassbeam     IBM     Oracle     Pentaho

SAS     Striim     Teradata     TIBCO     Vitria

 

Striim

Striim (formerly known as WebAction, Inc.) was founded in 2012 with a mission to “help companies make data useful the instant it’s born.” The company announced $20 million in Series B funding led by Intel Capital (total funding $32M) in September 2015. According to Striim, “the true value derived from the Internet of Things is not about the devices or even the fast communication among connected things. The value resides in the real-time analysis of the data that these devices generate.” I spoke to Steve Wilkes, founder and chief technology officer of Striim.

Upside: What is your company’s IoT vision?

Steve Wilkes: Our vision is to enable organizations to extract real-time value from IoT by collecting, adding context to, processing, analyzing, and visualizing IoT data through a single platform that scales to manage the extreme volume and velocity inherent in the Internet of Things. Customers should focus on insights they wish to obtain rather than the mechanisms for doing so, and factors such as edge processing, redundancy elimination, reliability, and security should be handled by the platform.

What products or platforms support IoT analytics and what is unique about your products?

The Striim platform collects IoT data using standard protocols and formats and processes, analyzes, delivers, and visualizes that data in real time.

Striim is an end-to-end, in-memory streaming analytics platform that enables organizations to get value from their data the instant it is created. The Striim platform can collect streaming data from many types of sources, including enterprise databases using change data capture, log data using continuous parallel collection, message queues, and IoT devices and sensors. This streaming data can be processed and analyzed before being delivered to other systems, alerts issued, or visualized via real-time streaming dashboards. This can all be achieved without any coding, utilizing an innovative UI for development and continuous processing functionality defined using a SQL-like language.

Can you provide one or two use cases where your products or solutions are used for IoT today?

One of the world’s largest cities has initiated a Smart Cities project to manage public transportation based on real-time population density through mobile-device monitoring. The city continuously monitors the density of cellular activity to determine hotspots within the city. Based on this changing density, they can alert state-run taxi drivers, dynamically allocate public transportation, as well as monitor and refine allocations and usage for the hotspots.

Here’s another example. A multi-national TV distribution company provides auto-scaling of infrastructure based on real-time demand. By utilizing streaming data from millions of set-top boxes, the organization has real-time insight into who is watching what. This information is used to autoscale their content delivery network to ensure that peak media loads can be scaled elastically in a geographically appropriate fashion. Coupling this with historical information provides insight into which channels viewers are switching to during commercial breaks or after a particular show so the company can dynamically predict unexpected loads on the switched channels.

Where can readers find more information?

Readers can visit www.striim.com.

Jump to: 

Datameer     Dell     Glassbeam     IBM     Oracle     Pentaho

SAS     Space-Time Insight     Teradata     TIBCO     Vitria

 

Teradata

Teradata offers big data analytic data platforms, analytic applications, and services. Well-known for data management, the Teradata family of products includes data warehousing systems ranging from a few terabytes in size to tens of petabytes. It acquired Aster Data (now Aster Analytics) in 2011 to provide large-scale data management and analytics capabilities. More recently, it acquired Think Big, a solutions and services company focused on Hadoop and big data. I spoke with Dan Graham, Technical Marketing Director at Teradata.

Upside: What is your company’s IoT vision?

Dan Graham: New sensors in new applications provide rich sources of data that, when integrated with other corporate data assets, will unlock the full value of IoT investments. Teradata’s products and people have worked with sensor data for over a decade, delivering the big ROI from the Analytics of Things.

What are your products and platforms that support IoT analytics?

We have a number of products that support IoT analytics. These include:

• Teradata Database is a parallel database capable of supporting thousands of users, in-database analytics, advanced compression, and many petabytes of data.


• Aster Analytics is an MPP database with SQL-MapReduce, SQL-Graph, direct SQL-on-Hadoop queries, plus over 130 built-in predictive analytics including time series analysis.


• Teradata Listener is a streams-based data mover and delivery service that can capture IoT data streams and store it into the data warehouse, Hadoop, sandboxes, and other repositories.

What is unique about your products or platforms?

Teradata invented in-database MPP analytics when it first integrated SAS PROCs into its parallel SQL execution. Since then, Teradata Database added parallel Fuzzy Logix and R in-database as well. In-database processing now includes nearly any language such as Ruby, Perl, and Python as well as scripts running in parallel under the control of a SQL innovation. Although proven scalability and performance are important benefits, the bigger benefit is that all business users can run in-database IoT queries from simple point-and-click BI tools.

Teradata Database provides ANSI Standard temporal table support.

Aster Analytics breaks all the rules for ANSI SQL user-defined functions. Instead of being limited to applying a UDF to a row at a time, Aster Analytics is able to invoke scripts, Python, Java, C++, plus over 130 advanced algorithms during MPP SQL execution. Using the SNAP collaborative optimizer, Aster Analytics can process complex IoT time-series correlations and join that information to graph analytics in a single query. Additionally, Aster Analytics provides native SQL-on-Hadoop processing, meaning it moves the processing to the data, not the data to the processing.

Teradata’s Unified Data Architecture includes major Hadoop distributions which is where many clients will first capture huge volumes of sensor data. Teradata QueryGrid can access that sensor data from Teradata Database or Aster Analytics.

Teradata’s investment in Presto open source is providing a high speed ANSI standard SQL-on-Hadoop platform for querying Hadoop. This Facebook codebase is a key component of Teradata QueryGrid development, offering architectural choices for the placement of sensor data on Hadoop or Data Warehouses.

Can you provide one or two use cases where your products or solutions are used today?

Condition based maintenance (CBM) is enormously popular with Teradata manufacturing customers. CBM uses sensor data to predict component failure on high-cost assets such as vehicles, ATMs, turbines, and compute servers. It’s interesting that Teradata hardware systems emit sensor data daily, which is sent back to a Teradata Data Warehouse for predictive analysis. Teradata Customer Support uses this to determine when a memory card, Ethernet adapter, or hard disk is likely to fail. This allows Teradata Customer Support to schedule repairs at the customer’s convenience instead of dealing with unplanned downtime. Teradata customers similarly apply CBM analytics to their assets.

Additionally, multiple utility companies are using smart meters for different kinds of analytics applications. The most popular use case is, of course, pricing-incentive rate plans based on peak time of day usage. Less well-known is the fraud detection use case. Thieves are known to steal entire smart meters or to break into one and switch out the SIM card identification of the meter and bill innocent electricity customers. With correlation algorithms, utility customers can identify the probable thieves.

Determining root causes of product failures is a third popular use of analytics. Manufacturers or CPG corporations, use sensor data to manage the production lines, some collect post-sales data, supplier data, and data from testing machines to correlate failure patterns. Our IoT customers include NCR, Union Pacific, Siemens, Volvo, PG&E, Southern California Edison, Western Digital, Micron Technologies, and the City of Vienna (Austria), to name a few.

Where can readers find more information?

Readers can visit www.teradata.com.

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TIBCO

TIBCO offers a “fast data platform” which makes data available in real time for analysis and action. The TIBCO Fast Data platform includes three broad product areas -- integration, analytics, and event processing. I spoke with Michael O’Connell, chief analytics officer at TIBCO about TIBCO IoT analytics.

Upside: What is your company’s IoT vision?

Michael O’Connell: To really make IoT work end-to-end, you need to be able to clean, merge, enrich, and shape data; perform visual and predictive analytics; and apply data prep and real-time math to streaming data. You need to integrate with surrounding systems -- for example to act on the results of analyses in a business process. You need visual dashboards for keeping track of interventions.

There are many data sources that need to be integrated in such business applications. It is not as simple-minded as some people and vendors make it sound. TIBCO has been doing end-to-end data integration, analytics, and event processing in the real world for years, before it was called IoT. The TIBCO Fast Data Platform brings together integration, analytics, and event processing to solve customer problems. The TIBCO Fast Data Platform has been gathering steam as our customers become digital companies.

What products and platforms do you offer that support IoT analytics?

There are three broad product areas supporting IoT analytics that are a part of the TIBCO Fast Data Platform. These products are enterprise class supporting numerous users and are capable of providing low latency and high throughput.

• TIBCO Integration: Our integration products combine best-in-class messaging capabilities with the ability to integrate, orchestrate, and expose (via APIs) numerous applications and technologies in private, hybrid, and cloud environments. Messaging products like TIBCO EMS and TIBCO FTL form the basis of high-speed, low-latency communications, and TIBCO BusinessWorks allows organizations to build a services layer based on architecture approaches such as microservices. BusinessWork's zero-code visual integration flows well, reducing the effort required to build and expose integration services. It also offers strong capabilities in the areas of real-time data preparation and transformation. TIBCO Open Spirit extends this environment with data connectors for specialized energy and equipment data sources such as Petra, Kingdom, and OpenWorks.


• TIBCO Spotfire Analytics: Spotfire is a pioneer and innovator in visual analytics. It allows users to manipulate data visually and iteratively, delivering true data exploration rather than simple visualization. Data preparation is built into this immersive process. Users can merge, transform, clean, drill, and enrich data inline without external tools from over 40 relational and big data stores. Spotfire can also bring together different kinds of data, such as geospatial data, weather data, and other contextual information.


• TIBCO Event Processing: This includes TIBCO Streambase, a streaming analytics platform that utilizes a visual programming paradigm to apply math to real-time data streams and TIBCO BusinessEvents, an event-driven rules platform that allows organizations to quickly build event-driven applications with real-time logic and reasoning. We also can deploy a real-time, in-memory data mart alongside these systems with our Live Datamart product; combining rich real-time visualizations with continuous queries and user driven alerts, actions, and responses. TIBCO’s Enterprise Runtime for R (TERR) engine interprets R code and R packages. This was built from the ground up by TIBCO and is much more performant than open-source R, especially for big data. TERR is embedded in both StreamBase and Spotfire.

What is unique about your products/platforms?

There are a number of features that make our products and platforms unique. The first is that our configurability is unparalleled in the market. Users can quickly integrate and shape their data. Second, our products are approachable; you can configure an end-to-end process and perform powerful analytics easily. The products also operate in true real-time. Of course, every problem has its own time granularity, but TIBCO messaging and streaming products can deal with data streaming at the microsecond level. Because of our strong integration capabilities, we are also able to marry streaming data with other kinds of data.

What are one or two use cases where your IoT products and/or solutions are being used today?

We have real-time IoT deployments in a number of areas. These include machine management and predictive maintenance to avoid failures. We do such condition-based maintenance for customers in medical imaging, wind energy, mining, oil and gas, and manufacturing systems. For instance, Occidental Petroleum is using TIBCO Spotfire and TIBCO StreamBase to maintain its artificial lift systems, which includes approximately 2500 submersible pumps. These pumps send data to local OSI-PI historians via telemetry, and these synch to a central historian system. Oxy has analyzed data in Spotfire to determine leading indicators of failure conditions. These leading-indicator models and thresholds are published to TIBCO event-processing systems for ongoing surveillance. As the data arrives from sensors, it is processed, and if a threshold is violated, members of the staff are alerted and business process systems are triggered.

Where can readers find more information?

Readers can visit www.tibco.com

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Datameer     Dell     Glassbeam     IBM     Oracle     Pentaho

SAS     Space-Time Insight     Striim     Teradata     Vitria

 

Vitria

Vitria, founded in 1994, provides a real-time streaming analytics platform called Vitria Operational Intelligence. The company believes that it is important to act on data quickly in order to provide value. Its platform is designed to trigger intelligent actions from big and streaming data. In 2015 it launched its IoT Analytics Platform that includes self-service tools and a temporal analytics engine. Mike Houston, director of product marketing had this to say about Vitria’s IoT analytics capabilities.

Upside: What is your vision for IoT Analytics?

Mike Houston: Analytics creates value from data. A significant challenge for many companies building IoT networks is to define and deploy analytics rapidly. Our goal is to remove those obstacles. Vitria’s vision is to provide a best-of-breed IoT analytics platform enabling simple and fast operationalizing of analytics that leads to smarter actions and better outcomes for our customers.

What products and platforms support IoT? What is unique about the platform?

Vitria’s IoT Analytics Platform provides a unified suite of advanced analytics tools supporting both real-time and historical analytics. In the near future, Vitria will launch an IoT Analytics Platform as a Service (APaaS), providing self-service IoT analytics in the cloud. There are a number of features that make our platform unique:

Real-time advanced analytics: Vitria can build analytics-processing pipelines consisting of multiple steps of predictive and prescriptive analytics over streaming data executed with sub-second latency. Vitria’s platform supports hundreds of predictive and prescriptive analytics techniques as well as intelligent action.

Self-service: Through visual modeling and wizard-like interfaces, OT analysts and business analysts can build analytic models easily and then quickly operationalize them.

Fast and scalable: Our platform elastically scales to the demands of IoT with support for millions of events per second with subsecond latency.

Rapid innovation cycle: Our platform enables extremely rapid analytics cycles consisting of iterative model building, operationalization, validation, and model refinement. Analytics cycles are measured in minutes, not months.

Can you provide one or two use cases where your products or solutions are used for IoT today?

Vitria’s IoT analytics platform is used for a wide variety of use cases. Some recent cases are:

• Predictive 1-1 marketing by tracking customer locations over time for Telcos
• Fraud detection and security analytics for smart meters
• Situational intelligence about electric and gas grid operation
• Supply chain visibility and real-time signaling for supply chain execution
• Predictive and preventive maintenance for manufacturing (e.g, a manufacturer of airport baggage scanners)
• Real-time driver behavior scoring for insurance

Some of our customers include O2, the largest mobile telco in the UK, which uses Vitria’s IoT Analytics Platform for more than two dozen use cases, including predictive 1-1 marketing for data roaming offers. Another is Eandis, Belgium’s largest energy distribution operator that uses Vitria’s platform for a real-time command center for IoT analytics and smart meter operations.

Where can readers find more information?

Readers can visit www.vitria.com/iot-analytics.

Jump to: 

Datameer     Dell     Glassbeam     IBM     Oracle     Pentaho

SAS     Space-Time Insight     Striim     Teradata     TIBCO