IoT data analytics

IoT data analytics offers actionable insights to operating technology data, breaking down and analyzing the IoT data and finding its value. With integration services and analytics tools, organizations are able to use the vast amount of data gathered from IoT endpoints and platforms to implement new business models and attain efficiencies.

OpenText™ Actionable Insights for IoT combines open source machine learning with advanced analytics to acquire, merge, manage and analyze IoT data.

Actionable Insights combines an identity-centric approach to securing, integrating and orchestrating data with world-class advanced and predictive analytics capabilities. Delivered as a managed service, the holistic Actionable Insights solution provides users the insights they need to make better business decisions based on their IoT data.

Enables users to design, deploy and manage secure, interactive applications, reports and dashboards that combine disparate IoT data sources. Supports a high volume of users and allows content to be easily embedded into any application with integration APIs (including REST and JavaScript).

Transforms and orchestrates structured and unstructured data into actionable insights with relevant, role-based graphics and visualizations to easily identify and interpret information trends.

Exports and integrates disparate IoT data to create personalized analytic dashboards and interactive visualizations within enterprise applications, workflow and processes for maximum impact.

Leverages a full range of easy to use self-service capabilities. Users can choose from built-in functions that emphasize simplicity and ease of use or sophisticated, powerful reporting with the ability to add new data sources on the fly.

Make better, more timely decisions with easy-to-understand, interactive dashboards, reports and visualizations of operational data.

Streamline processes and improve business performance by monitoring key metrics in realtime. Identify variances, issues and opportunities with alerts and take action on insights.

Leverage machine learning from past patterns and events to anticipate potential failures or issues to mitigate and manage risk and cost.

Use advanced, out-of-the-box identity and access management functionality for rapid project go live and ensure that analytics results are securely accessed by relevant stakeholders.