C3 IoT announced this week Version 7 of its enterprise software platform for big data, predictive analytics, artificial intelligence (AI), and Internet of Things (IoT) applications, with new tools and enhancements that significantly increase the productivity of application developers, data scientists, and business analysts by enabling them to all work on the same framework.
This productivity improvement reduces companies’ IT expenditures and speeds time to market of predictive analytics software applications that perform AI and machine learning at scale to recommend actionable business insights and facilitate digital transformation.
By leveraging telemetry, elastic cloud computing, analytics, and machine learning, C3 IoT brings the power of predictive insights to any business value chain. C3 IoT also provides a family of turn-key SaaS IoT applications including predictive maintenance, fraud detection, sensor network health, supply chain optimization, investment planning, and customer engagement.
Version 7 of the C3 IoT Platform is rolling out to enterprise customers worldwide in Q1 2017 with advanced capabilities spanning five elements of the C3 IoT Platform – data science tools, artificial intelligence algorithms, application development tools, edge analytics, and platform administration – that increase user productivity and accelerate the delivery of AI and IoT applications.
C3 IoT now offers C3 Ex Machina, a visual analytics and machine learning development tool that simplifies and speeds big data exploration and predictive analytics modeling. Powerful yet intuitive, C3 Ex Machina empowers data scientists and business analysts to extract actionable business insights, without writing any code.
It also delivers native support for Python and R, allowing data scientists to leverage their programming language of choice and push their code back to production in the C3 IoT Platform without re-writing any code.
C3 IoT is expanding on the AI and machine learning capabilities currently integrated in its platform with additional deep learning technologies and more advanced analyses that increase the precision and accuracy of predictions.
C3 IoT also added image processing for object and facial recognition at the edge; natural language processing (NLP) for analyzing text-based data such as hand-written notes and work logs; expanded support for libraries of machine learning algorithms; and a machine learning pipeline that makes it faster and easier to develop and deploy machine learning models and publish them back to the platform.
The C3 Type System, a high-level abstraction layer that enables disparate users to interact with the same metadata-driven architecture for defining and developing applications, now offers native HDFS integration to connect to customers’ data lakes as well as several enhancements that improve performance and optimize storage.
A new version of C3 IoT’s metadata-driven, web-based development toolset, C3 Tools, improves the user’s ability to define integration processes, create and extend data models and analytics, build machine learning classifiers, and rapidly develop user interfaces. A new Eclipse plug-in gives developers additional tools to develop, deploy, and debug applications on the C3 IoT Platform.
In addition to Cassandra, C3 IoT now provides full support for AWS DynamoDB, a fast and flexible NoSQL database service for applications that need consistent, single-digit millisecond latency at any scale. It also delivers integrated profiling and debugging tools enable developers to resolve issues and identify performance bottlenecks; with improved roles and responsibility management that simplify administration and improves security.
C3 IoT has streamlined and improved platform administration tools, including the ability to manage environment configurations, manage auto-scaling configurations, and enable self-healing of common issues.
“Enterprises have made significant investments in data lakes, data scientists, and application developers on the road to digital transformation,” said Ed Abbo, president and CTO, C3 IoT. “However, in many cases, developers and data scientists operate in isolation, which can delay and even derail the delivery of AI and IoT applications that work. Version 7 of the C3 IoT Platform bridges that gap by enabling disparate teams to operate on the same platform and object model. This boosts productivity tremendously, reducing our customers’ IT costs while speeding the realization of predictive analytics results.”
“C3 IoT successfully addresses a number of challenges that have plagued enterprises in the past with respect to traditional approaches to Machine Learning,” said Holger Mueller, vice president and principal analyst at Constellation Research. “With C3 IoT, data remains in place, gets automatically updated and refreshed, and thus Machine Learning capabilities are no longer the domain of a small clique of advanced users. Business users are empowered to create their own Machine Learning-powered analytical applications and can plug them in to transactional applications as needed.”