Analytics has never been more important as the amount of data grows dramatically; but data only has value if we actually put it to use - which means being able to analyze it and react to what it tells us.
Being able to spot and react to events in real-time is critical in making your business more agile; whether it’s retaining customers, spotting identifying and resolving problems in the supply chain, or using predictive maintenance.
Join us at Software AG’s 2018 Product Release Virtual Conference on October 9-11th to learn how to do this - and to hear about our new features, innovations and vision of the future for our data and analytics platform.
In this conference we will be introducing an integrated platform that includes visual, streaming and predictive analytics along with messaging for integration and an in-memory data store for performance.
This integrated platform delivers a faster ROI and reduces both cost and risk. We are making this really, really easy to use with graphical tooling for business people and also the ability to connect to other systems, as well as IoT devices, to maximize the value of your data.
At Software AG’s 2018 product release we will demonstrate our future vision for analytics, including:
- Making advanced analytics for real-time data available to everyone.
- Leveraging our world-leading integration capabilities, making it easy to deploy and integrate these applications with other enterprise apps.
- Making the platform not only available in the cloud, but as a SaaS offering too.
Here are some of the additional capabilities we’ve added this year:
- Support for connectivity using Kafka within our streaming analytics component, Apama.
- Updated support for Docker, which means Kubernetes can now be used.
- We now support Prometheus integration, the open-source monitoring and alerting system which can monitor correlators via the REST interface, a JSON plugin helps in handling JSON payloads and a Cumulocity IoT transport plugin is also now built into Apama.
- You can now execute Python scripts within the correlator, which makes it possible to re-use the extensive libraries of third-party Python libraries out there, for example, in Machine Learning.
- We’ve also made very significant performance improvements to the EPL language which can now compile EPL to machine code for specific CPU architectures, for the fastest performance yet.
- For our capital markets customers, we’ve made several updates to the adaptors including Bloomberg, Reuters, BM&F, and CME.
- For machine learning and predictive analytics, we’ve added support for several deep learning architectures for use-cases such as object detection, damage detection, quality control and financial trading.
- We also created and released Nyoka, an open-source Python library that can export PMML from Python-based Machine Learning and Deep Learning environments, and these models can in turn be deployed by our Zementis Predictive Analytics component in the platform.
- We’ve updated the REST API to the OpenAPI 2.0 standard and you can now run Zementis on Android.
We will also demonstrate our forthcoming Analytics Builder and a ’connected store’ use case. In addition, we will be discussing real-world examples of our customers and use cases where they are using the data and analytics platform. This includes Citibank, Bitmarck, Greyhound and Royal Dirkzwager.
Register below to come see our vision for analytics at the at Software AG’s 2018 Product Release Virtual Conference on October 9-11th.