Powerful Analytics & Decision Making at the Scale of the Internet of Things
Use modern solution and technology to architect IoT data and machine learning
With all the data generated from connected devices, sensors, and IoT ecosystem, it is important than ever to study this data in real-time, learn how these assets are performing, and provide valuable insights for critical decision making. An agile-based robust framework of Lyftron and scalable architecture of next-gen data warehouses allow transforming the structured and semi-structured IoT data and accelerate machine learning.
WIthout impacting on the IoT sources, you could load data to multiple destinations, connect them to numerous BI tools and prepare analytics reports in a few minutes. Lyftron makes it possible to handle the volume, diversity, and streaming nature of IoT data, enabling enterprises with real-time analytics and machine learning. Lyftron’s smart data architecture processes machine and sensors data in no time and helps you predict key outcomes, ensuring you’re always ahead of the curve. Work with the chosen web service platform and manage large data volumes at an unprecedented low cost and effort.
Eliminate the complexity with Lyftron's migration simplicity
Making the best of data generated from IoT devices and Machine Learning
Predicting the behavior of IoT devices is of utmost importance in order to plan their maintenance and avoid failure. Lyftron uses advanced analytic techniques that leverage historical data to uncover real-time insights and predict future events associated with connected devices.
Data management with Lyftron allows creating a single view of all IoT data sources and data warehouses. Join disparate data sources in real-time or build federated views and materialize them to avoid data source overloading.
Data Management Made Easy
Lyftron’s enterprise-grade data virtualization helps to simplify the data management process through a centralized secured layer and empower users to search, catalog, and govern the unified data.
Logical Data Layer
Lyftron acts as a data layer for analytics that combines traditional data loading with logical data warehousing to improve collaboration and deliver data-driven results needed to handle today's IoT and machine learning data volumes.
Bigdata Processing and Machine Learning
Modern integration with Lyftron enables rapid, real-time ingestion of high-volume data from varied IoT sources — and extremely high performance. You enjoy have full access to every data set from every source.
Real-time Actionable Insights
Data consumers access the real-time information of a huge volume of IoT data coming from any source, at any time and get a holistic view of their enterprise for critical decision making.
Embrace data innovation with data monetization
Simply convert your data into monetization revenue system by enabling your customers, employees, suppliers, providers, consumers to utilize secure agile platform for their data transfer. Gone are the days when enterprises share the data with writing custom API, use FTP process and email for data exchange. Lyftron gives any organization the ability to securely share data, and receive shared data, while eliminating the cost and headache of traditional data sharing methods. You can create your own data hub with secure access to live and governed data. You control who provides the data, who can view the data, and who can access the data.
Lyftron provides better security and governance on your data to enables enterprises to share with ease. Lyftron Data Sharing Hub acts a enterprise data security layer where enterprise can control how do they want to share their data. Lyftron provides an easy and secure way for organizations to become data providers and therefore monetize their data to create new revenue streams. In addition, every Lyftron customer has access to the Lyftron Data Providers, where they can acquire third-party data, combine it with their own data, and gain a level of insight not possible before. Just imagine if all the barriers to sharing and monetizing data disappeared. What new insights and opportunities would emerge that would transform your organization?