2021 promises to be another year of growing IoT opportunities for system integrators. With an ever-broadening range of affordable connectivity, device management and sensor options, the ability for system integrators to rapidly develop and deploy solutions that fit their customers’ needs is greater than ever. Here are the three key strategies that system integrators can do to capitalize on IoT market growth in 2021. 1. Develop prototypes and proof-of-concepts (POCs) that get your customers engaged right from the start. According to a recent survey, up to 60% of IoT projects never make it beyond the POC stage. Lack of time, technical complexity and running out of budget are the key reasons why most IoT project ideas fail. By developing field-ready POCs that customers can test drive, system integrators can engage customers support and feedback from key deployment constituencies at the onset of an IoT project. In the near-term, this puts you ahead of competition and in the long-term, this can help your team avoid costly “feature creep” that can kill a project before it even gets over the finish line. 2. Leverage ready-to-use solutions whenever possible. Let’s face it – each customer feels like their situation is special. At the same time, most customers deploying an IoT project or network want two things: To get their project deployed as quickly as possible. To leverage as much of their existing machine network as part of the solution to avoid unnecessary rip and replace costs. Leveraging ready-to-use sensors, device gateways and software, such as Machinechat’s JEDI One ready-to-use edge IoT data management software, can enable system integrators and developers to achieve several outcomes: More quickly develop field-ready POCs and transition to field-ready deployments without having to reinvent the wheel. Reduce technical resource complexity and cost by allowing developers to spend less time on building IoT solution layers and more time on the user experience and integration with enterprise requirements. By combining off-the-shelf or ready-to-use sensors with ready-to-use IoT software, developers and system integrators can spend less time and resources on developing custom middle layer software – and more time on enhancing the user experience and integrating the IoT project with a customer’s enterprise business applications and goals. Allows customers to adapt and add legacy investments to their IoT strategy. 3. Focus on simplifying your customers’ experience and path to expansion. IoT is an industry that is ripe for innovative ideas – but system integrators and developers need to be careful not to confuse the concept of innovation with customer success. For an IoT solution to be successful and desirable to a customer, it must be: Simple to implement, maintain, control and expand; Cost-effective and timely in delivering a quick path to ROI; and Easy to use, deploy and incorporate into their existing enterprise infrastructure. The bottom line? IoT remains a market with an abundance of opportunities (and growth) for system integrators who can move quickly to deliver field-ready solutions that are aligned with not just your customer's technical needs - but that can be easily adapted to their near and long-term business needs. Want to learn more about how your team can develop and deploy IoT projects faster with ready-to-use IoT software? Stay up to date with Machinechat by signing up for our newsletter or check out our other blogs.

With more and more devices and sensors being connected to the Internet to communicate with cloud-based applications, the security of IoT networks continues to be a topic of concern. Recent research from IoT security firm Forescout found that 33 flaws in a single popular open source implementation of an Internet protocol stack could potentially expose millions of embedded devices to participate in denial of service, ransomware and information interception attacks. Many of the devices may be difficult if not impossible to patch. At the same time, everyone knows that IoT can deliver significant business value – so how can system integrators and IoT developers design projects that won’t have IT administrators ridden with anxiety? Deploying a Virtual IoT Gateway at the Edge Can Reduce IT Anxiety (and Deliver Cost Savings) Edge processing in IoT networks is increasingly seen as an effective strategy for managing IoT data on the local level; at the same time, many devices and sensors were not designed to support data management processing and application integration. Most companies also don’t have the ability, desire (or budget) to rip and replace machines simply to make them “IoT ready.” A virtual IoT gateway is a software application that is deployed at the edge, as a service inside a cellular modem, network access point, a single board computer or a virtual machine on a server. Installing a virtual IoT gateway with data management capabilities between your devices and the outside world, delivers several advantages: By aggregating IoT data traffic into what can and needs to be acted upon locally – and what data needs to be transported outside the on-prem network, IoT developers ensure that only the right data goes to the right application (or the cloud) at the right time. Localized data storage allows OT and IT admins to preserve data records and audit trails while controlling how data is managed and integrated with business applications. Reduces cloud data processing costs. Enables data extraction from legacy systems without exposing them to the outside world, reducing the overall cost of IoT implementation and enhancing IoT project ROI. Machinechat JEDI One software functions as a virtual IoT gateway that allows developers and system integrators to create safer and efficient IoT networks without the need to spend weeks and months developing and testing custom software to integrate the heterogeneous devices and sensors with their line of business applications. Machinechat JEDI One is: Single binary software solution with no libraries to support or maintain makes it easy for integration into network modems, gateways or installed inside a virtual machine. Fully integrated HTTP, TCP/IP data collectors and MQTT broker make it easy to start ingesting data in minutes . Custom plug-ins allow developers to add virtually any sensor or device without altering their native protocols Easy drag and drop menus allow developers to quickly configure rules-based monitoring, data visualization, customizable storage with zero programming. Configurable local data storage with retention controls enables admins to maintain full control over their data. Want to learn more? Stay up to date on the latest news and articles from Machinechat by signing up for our mailing list here.

It’s been over a year since I wrote about making IoT accessible to Every One – so where are we today? Here’s the good news: Connectivity is cheaper than ever and the options available continue to grow Sensors and hardware continue to become more affordable Data analytics tools are becoming more sophisticated and vertically-oriented A recent survey done by Eclipse Foundation indicated that commercial IoT deployments continue to grow at a steady pace (but are still not ramping to the hype levels previously predicted). The ROI on IoT investments continue to improve, with more than 40% of businesses reporting multiple positive outcomes from their IoT investments, including improved business controls and business processes, as well as identifying new products and services. And the not so great news? Implementing an IoT project continues to be technically complex and requires significant investment in time, resources and skills. A recent article estimated that more than half the cost of developing an IoT project is in software development (that’s just the cost of development and does not include on-going maintenance) and data storage, which if you use the cloud can add up to significant recurring costs. Given these barriers, it’s not surprising that a recent survey found that less than 10% of small businesses and less than 30% of middle market companies have adopted IoT technologies. Yet these are the very companies who could benefit the most from the efficiencies and cost savings that IoT can deliver. The Three Main Challenges With IoT Software Today Today, there are a number of IoT software solutions available for data collection, monitoring, visualization, and storage management. So why are IoT solution developers struggling with them? · Complexity. Most IoT software today have become cloud-based one-size-fits-all solutions. Built to address the needs of large customers such as the fortune 500s with sophisticated requirements and thousands of developers, existing IoT software solutions quickly overwhelm small teams of IoT solution developers at small and mid-market companies. Many solutions require that developers use a specific type of network protocol, programming language and spend significant time in configuring multiple services and API layers. On the other side, there are several open source software solutions. While it is cheaper to get started with open source software, it takes significant time and resources to qualify, modify, stitch and integrate discrete open source components from different authors into a cohesive solution, productize it and the support it in the field. · Lack of Control. Most commercial IoT deployments require control over their data. The vast majority of today’s IoT data management and integration solutions require that data be stored in the software provider’s cloud. · Recurring and Never-ending Subscription Fees. The vast majority of IoT solutions today are SaaS based, requiring that IoT solution developers and their customers committing to never-ending monthly subscription fees that can quickly add up. The Three Things IoT Solution Developers Want in a Software Solution · Configuring, Not Coding. For small and mid-market companies with small teams, speed and efficiency are the competitive advantages needed to stay relevant in the marketplace. A ready-to-deploy software solution that can be configured and adapted to the IoT project at hand allows them to capture opportunities quickly, without spending thousands of man hours in custom software development. · Data Control. Not all data needs to be in the cloud. More importantly, today’s IoT solution developers and users want to be able to control where, when and how long their data is stored and used. · Cost Simplicity. Remember the days when you just paid for a software license once and kept using it for as long as you wanted? You didn’t have to worry about losing access to everything when you cancelled the subscription Also you could upgrade when you actually wanted and needed to. JEDI One for Windows, Linux and Mac: Affordable, Accessible and All-in-One In December 2019, we introduced JEDI One for Raspberry Pi, which was the industry’s first affordable and easy-to-use IoT software solution for Raspberry Pi innovators and those looking to explore what types of IoT ideas they could come up with. This week, we launched the next chapter in the promise of easy-to-use, affordable, and accessible IoT software solutions: JEDI One for Windows, Linux and Mac. Designed for the field application engineers, developers and solution architects on the frontline of creating and deploying IoT projects, JEDI One for Windows, Linux and Mac enables them to quickly bundle comprehensive data collection, visualization, and monitoring into any IoT project in minutes. No more libraries to build or maintain, no custom APIs or software to write, no new programming languages to learn and you maintain control over your data – where and when it goes, where its stored and for how long. What’s even better? The cost. Download our free version (no trial period, it’s just free forever) or purchase a premium version for the one-time license cost of USD $79. So what are you waiting for? The time for IoT for Every One has arrived...join us and let us know how you’re doing and how we can help you be successful.

In our previous blog, we discussed how to eliminate the technical complexities around collecting IoT data, one of the six steps that connected device and sensor data must go through to be transformed into meaningful action and ROI. Once IoT data can be collected, it must be: Monitored to allow for quick response to changes and remediation. Visualized to observe trends and diagnose issues. Today, many IoT solution architects and developers must choose between either: Spending several months and thousands of dollars in developing UI, frontend and backend code for building custom data monitoring and visualization applications for each IoT project; OR Committing to a cloud-based IoT platform and dealing with: Fitting into a one-size-fits-all platform Ongoing bandwidth costs Recurring subscription fees Lack of control over upgrade cycles, forcing expensive field updates and support, warranty resets and re-training, subscription fee hikes Complex and always changing privacy policies Vendor lock-in for the life of the IoT solution Bottom line: the existing options for most IoT solution architects and developers are often complex, inflexible and prove to be quite expensive over time - definitely beyond the reach of most organizations that can benefit the most from IoT. IoT Data Monitoring and Visualization Should be Accessible and Affordable To All Organizations that have deployed IoT solutions continue to benefit from reduced operational costs, improved quality and enhanced customer experience. For every organization to realize the benefits of deploying IoT solutions, an IoT data monitoring and visualization software must be: Read-to-use, but configurable to adapt to the use case Deployed in the network or on-premise to save on bandwidth costs and comply with data privacy laws Provide control over software upgrade cycles Ready-to-use solutions like Machinechat’s JEDI One software, deliver an all-in-one experience for data collection, monitoring and visualization that is: Deployed in the network or on-premise Configurable to support multiple data collection protocols, data monitoring rules and data visualization dashboards - without the need to change device or sensor hardware or firmware Upgradeable when the customer and target environment is ready, through a perpetual license - not an all-or-none ongoing subscription Easy to bring data in or take data out of the system through the use of open data formats Want to learn more? Learn about how edge computing can accelerate your path to IoT ROI or sign up to get the latest updates on Machinechat news, product releases and beta programs.

Transforming device or sensor data into information that can be meaningfully acted upon (either manually or automatically) requires a journey through six steps: The source of the data must be Connected to the IoT network; Data must then be Collected and transported to the right applications; Visualized in a meaningful and appropriate context; Monitored to allow for quick response to event changes or the need for remediation; Analyzed to identify opportunities for improvement or operational efficiency; and Actualized to create new business opportunities and realize ROI from the IoT investment. Collecting data from multiple devices, sensors and machines – and making sure the right data goes to the right application at the right time – is where many IoT solution architects must resolve multiple complex issues: What data to extract Unlike (most) people, sensors and devices output data indiscriminately. While the average human being consumes and creates less than 1 GB of data per day, a single sensor can output 6GB per hour. Not all data is relevant – and sending it all to the cloud to be organized can become an expensive strategy. What format to put data in In the world of connected devices, IoT data is not simply just “data”. The format that data exists in a single sensor A is not the same as the data from machine B or even sensor C. For IoT data to become useful, it must be shared and used across multiple applications and stakeholders. What applications to send data to and when Just as not all data is relevant, not all data is going to the same application (and some data may need to be shared across multiple applications and stakeholders) and is needed at the same time. While an OEM of a device may only need data to be sent when a systemic error occurs or when providing maintenance, a local operator may need to be able to see device data on a daily or even hourly basis and a business analyst may need to have a subset of the same data imported into a different application in a weekly or monthly report. Each extracted data stream has value – but to whom and when do they need it? How long and how much data should be stored Most devices and sensors have limited storage capacity on the local level. Still for IoT deployments to deliver enhanced value, sensor and device data should be stored so that it can be accessed and viewed in relation to the operation of other devices and sensors on the network, both in real-time and historically. Solution architects must determine the length of time that data needs to be stored locally on-prem, in the cloud or off-site. IoT Data Collection Complexity = Siloed Projects That Deliver Limited Value For IoT solution architects, creating a data collection solution to address the above issues can result in the need for extensive time and effort to be spent on developing APIs, custom programs and firmware to extract, format, transport and store data between: the device and local applications the device and the cloud local applications and the cloud More importantly, for data from the IoT network to be useful, data streams from multiple sensors and devices must be visualized and monitored together – creating more complexity for solution developers. It’s not surprising that given the complexity, many IoT projects remain siloed and separate from the enterprise – limiting the business value they can deliver. Network-Integrated Data Management Can Simplify IoT Data Collection For IoT solution architects, a ready-to-use data collection solution should include: The ability to easily configure any device or sensor for data extraction with minimal to zero coding The ability to schedule data reporting and monitoring via email and SMS Transformation and storage of sensor and device data into a data format that can easily be accessed and used across multiple platforms or applications Allow for on-prem and cloud optional deployment Be scalable Network-integrated data management solutions leverage the power of edge computing to simplify IoT data collection and provide IoT solution architects with a scalable solution that can allow them to more quickly deploy IoT networks and projects. By putting data management intelligence on the edge of the network infrastructure, solutions like Machinechat’s JEDI IoT Data Manager, solve these data collection issues: Eliminate the need for altering device and sensor firmware or hardware Enable easy-to-deploy extraction of sensor and device data in its native protocols Allow for a single pane visualization and monitoring of data from multiple devices and sensors in minutes without the need for custom programming Enable automated local storage in CSV formats – allowing the data to be easily exported and shared across multiple applications Allow data to stay on-prem and at the same time, enable data to be stored or transported in a cloud-ready format.

Last week, the Raspberry Pi Foundation announced the availability of a new Raspberry Pi 4 equipped with 8 GB of RAM. This is great news for Raspberry Pi enthusiasts, especially those seeking to develop projects to solve real world problems. Raspberry Pi has gotten increasing attention in recent times as an inexpensive but potentially powerful single board computer that can be used to prototype commercial ideas – from operating as a car computer to powering ventilators for COVID-19 patients. Still, in many cases, Raspberry Pis are only used for prototyping. Why? The answer is simple and it starts with the data. While Raspberry Pis today can handle processing the data throughput of many commercial applications, creating the programs to visualize and monitor the data is often a time-consuming and technical task. For example, just creating a single web-accessible, real-time line chart (like the one below) for tracking a temperature sensor would require a developer to spend significant time and effort deploying a web server, installing a database and writing code to extract, format and print data. It’s no surprise therefore that more often than not, Raspberry Pi enthusiasts find themselves explaining “what that means” when showing off their project or prototype. While there are a number of ready-to-use tools for visualizing IoT data, these often require an on-going subscription and can still require developers to write APIs to connect their Raspberry Pi and any connected sensors or machines to a third-party cloud. Also most of these tools allow for viewing data only in real-time and may require subscribing to additional services (and writing additional APIs) to monitor your data. Here at Machinechat, we believe that the data should look as sharp as the Raspberry Pi project itself is. Furthermore, we think it should be obscenely easy to enable developers to see, manage, monitor and access the data from their Raspberry Pi projects in minutes. And they should be able to do it without needing a cloud and pesky monthly subscription fees. A good friend of mine once gave me a great piece of advice: “If you’re planning a dinner party, before you start cooking, set the table first. That’s the first thing that people see when they come in and a well set table not only communicates that you’re prepared but tells your guests to expect something special.” There are many thousands of Raspberry Pi ideas out there. And just as a beautifully set dining table can enhance the dinner experience, a professional and high functioning data experience can go a long way in communicating that a Raspberry Pi IoT concept is both field-ready…and ready for adoption in the marketplace.

As more than one-third of the world’s population is under stay at home or lockdown orders, the importance of being able to quickly build and deploy infrastructures that can connect data, machines and people is more important than ever. Internet of Things (IoT) technologies can provide the ability to ensure that life and systems can continue even during a global crisis. But for these solutions to be quickly deployed, it is critical that developers be able to leverage true plug-and-play IoT tools that can allow ideas to go from zero to field ready in minutes and not months or years. For example, the COVID-19 crisis has necessitated the need for local and federal governments to build field hospitals that can help to alleviate capacity issues as traditional hospitals are stretched. Often in less than a week, hospitals must be designed and built from the ground up in non-traditional environments ranging from parking lots to conference centers. Having the right communications and critical monitoring systems in place is no less critical in a field hospital than it is in any other medical environment. The challenge is two-fold: 1) these new “hospitals” are not comprised of fixed rooms and facilities designed for medical use; and 2) the lack of time and technical resources available to spend months and years integrating many vertical and proprietary applications. When minutes count, the need for IoT tools that are truly “plug and play” can go a long way to quickly make the leap from idea to field-ready and deployable. Plug and play IoT tools enable developers and solution architects to configure connectivity and data management with Minimal to zero coding No alteration of a machine or sensors firmware, software or hardware Intuitive user interfaces that require minimal training to understand Flexibility to allow for tool customization and plugins by power developers Can be deployed and used in minutes In the field hospital example, combining a ready-to-use, cloud optional software solution like Machinechat’s JEDI IoT Data Manager, an IoT solution architect would be able to quickly use off the shelf sensors and gateways to deploy a critical monitoring infrastructure in a field hospital within hours. This would allow field hospital operators to ensure optimal environmental conditions, track both human and equipment resources, and track and share data with key stakeholders. Recent events have demonstrated that the ability to act quickly on accurate data can have a huge impact – not just in saving lives but in also ensuring that crises do not result in economic and other devastation. Being able to deploy an IoT project quickly will require plug and play tools that meet the above criteria and enable developers to focus their attention instead on creating applications that deliver enhanced IoT network outcomes and results that go beyond just “connecting the data”. At Machinechat, our focus is on delivering plug and play IoT data management solutions that allow solution architects to quickly deploy IoT projects in minutes, not months. And right now, we need these ideas to become reality faster. The time for plug and play IoT is now!

Here at Machinechat, one of the concepts we talk about is “getting the right data at the right time to the right application.” We often discuss this concept in terms of making sure that the data from the connected “Internet of Things” is timely, accurate and directed to the right source or decision-making application. Today, the world is dealing with a global pandemic that has demonstrated very clearly that we - human beings - are very much our own connected network, where the behavior of one can have an impact on many others. In other words, we – literally, every man, woman and child on Earth – have become the “application” whereby the spread of this horrible virus can stop. To that effort, below is a compiled list of online resources that can provide factual information related to COVID-19. We hope you find these resources useful and on behalf of the entire Machinechat team, we hope that you and your families will continue to stay informed and healthy. International Resources World Health Organization, COVID-19 Updates: https://www.who.int/emergencies/diseases/novel-coronavirus-2019 United States Resources U.S. Center for Disease Control: The CDC provides the latest federal government guidelines and updates on COVID-19 mitigation and medical information in the United States. C-Span C-Span provides unedited coverage federal government coronavirus briefings and testimony. In addition, it includes (to a limited extent) coverage of state, Canada and Europe briefings on COVID-19 developments. John Hopkins University Coronavirus Tracker: https://coronavirus.jhu.edu/ US County and Local Municipality COVID-19 Updates To receive up-to-date emergency and government updates (including for COVID-19) for your local US municipality, Nixle is an excellent resource. You can sign up for free automated email and text updates for up to 5 US zip codes by going to: https://www.nixle.com/ State COVID-19 Resources Click on the links below to access state-level COVID-19 information resources Alabama Alaska Arizona Arkansas California Colorado Connecticut Delaware Florida Georgia Hawaii Idaho Illinois Indiana Iowa Kansas Kentucky Louisiana Maine Maryland Massachusetts Michigan Minnesota Mississippi Missouri Montana Nebraska Nevada New Hampshire New Jersey New Mexico New York North Carolina North Dakota Ohio Oklahoma Oregon Pennsylvania Rhode Island South Carolina South Dakota Tennessee Texas Utah Vermont Virginia Washington Washington DC West Virginia Wisconsin Wyoming

You’ve got an idea, a project that’s been stuck in your head for awhile. Maybe it’s building a weather monitoring station, power consumption meter or something else. With over 30 million sold to date, Raspberry Pis offer an inexpensive and powerful way for makers, engineers and inventors to take their ideas and make them into reality…so why is it that when I talk to many developers, most of the Pis they own are sitting in their closets collecting dust? It boils down to one thing: Time. In addition to setting up a Raspberry Pi and connecting the sensors needed for a project, most developers must also invest time and effort into the following: Time needed to learn the one or more languages or programming necessary to write code to transport and translate data from project sensors’ native protocols to the Raspberry Pi Time needed to program the Raspberry Pi to visualize and monitor the data in a meaningful way Time needed to create a rules engine for automatically monitoring the application data Data is the oil that feeds and allows applications to be actualized – but you shouldn’t have to reinvent a pipe every time you want to build a new type of rig. At Machinechat, our focus over the last year has been on creating a simple software solution that enables developers to focus more time on their idea (and making it brilliant) than on having to spend valuable time and effort on writing custom code to get the data from their project collected, visualized, and monitored. With Machinechat’s JEDI One single binary, developers can start collecting, visualizing and monitoring sensor data via their Raspberry Pi within minutes of connection. Even better, data is easily transformed – with zero programming or coding time spent – into beautiful data or system view charts that deliver the polished, sophisticated look your project idea deserves. (After all we’re in 2020, not 1984.) Additional features include: Drag and drop rules monitoring that allow for email and SMS notifications You own your data – no need to have your data pushed to the cloud or controlled on someone else’s cloud service. No subscription fees – JEDI One is free or you can upgrade to our premium version for a one-time license fee of $39. As a 20+ year veteran working with tech companies, I’m convinced that the next great idea won’t come from a large tech behemoth…but from developers who are equipped with affordable, robust solutions and tools that allow them to transform their ideas from “resolutions” to reality quickly. With Machinechat JEDI One, we hope to enable today’s makers, engineers, and inventors to do just that by delivering the world’s best data collection, visualization and monitoring software solution. Click here to learn more about Machinechat JEDI One for Raspberry Pi and to download a free copy. Join our Monitoring in Minutes contest and you could win a $100 Amazon or Visa gift card!

Today there’s a lot of discussion around edge computing and its role in helping to bring data analysis and management closer to where devices live (and work). For IoT solution architects, edge computing can deliver significant benefits in reducing latency, eliminating device exposure to Internet threats and controlling cloud costs by dramatically reducing the amount of data transmitted and processed using cloud providers infrastructure. One area that edge computing is being applied to is IoT data management. In an IoT deployment, edge computing data management can be integrated primarily in two ways: On the device or sensor itself; and In the network on routers, gateways or access points (or what we call “network-integrated data management”). While many OEMs are starting to develop and deliver new machines and sensors that have the ability to do some edge-computing functions and processes (such as limited device data management), many of today’s currently deployed industrial machines and sensors are not able or have limited ability to be adapted for edge computing. Using a network-integrated approach to edge computing data management enables IoT solution architects to address heterogeneous IoT enterprise data issues by: · Eliminating data silos. Network-integrated data management provides the pathway for IoT developers to integrate different device and sensor data streams into the heterogeneous enterprise workflow. By allowing for different data streams to be automatically directed to the right business applications at the right time, companies can more quickly act on IoT data analysis and less time on moving data from one point to another. · Enabling existing machine investments to participate in IoT projects. One of the largest challenges most companies face when considering an IoT project is the cost of upgrading or ripping and replacing existing machines. This often results in many companies choosing to limit their IoT deployments to new machine investments – and subsequently, reducing the advantages that a fully realized IoT strategy can deliver. With a network-integrated data management solution in place, IoT solution architects can easily integrate both existing machine investments and edge-enabled devices. Also, by integrating a ready-to-use data management solution in the networking infrastructure, adding new machines and sensors to the heterogeneous machine network becomes a configuration exercise – versus one that feels like remodeling the Eiffel Tower. · Reducing or eliminating the need for custom programming and software development. Even with edge computing-enabled devices, IoT solution architects must spend a lot of time and resources on developing and maintaining custom firmware, APIs and programs to connect machine data to business applications and the cloud. Ready-to-use network-integrated data management solutions, like Machinechat JEDI IoT Data Manager, eliminate the need for coding and allow IoT solution architects to focus more time on transforming IoT dataflows into business productivity solutions. The bottom line? Incorporating a network-integrated data management approach enables organizations to: Bridge the gap between OT data and IT applications and the enterprise business workflow. Extends the reach of your corporate IoT strategy to include existing and future machine and sensor investments. Reduce the cost of IoT deployment and on-going cloud transactional costs. Integrate and deploy IoT projects faster – and accelerate their path to IoT ROI. Want to learn more? Check out our blogs on the four reasons why network-integrated data management makes sense and how to build a data management application. Stay up to date on Machinechat's latest news and updates by signing for our mailing list here.