TrendMiner's ContextHub is built around the structure of OSIsoft PI event frames and asset framework, broadening use and usefulness of contextual information for root cause analysis (RCA) and operational performance monitoring.
The TrendMiner 2023.R1 release focuses on enhancing IT/OT convergence by simplifying the integration of various data sources. Digital twin manager: Users can quickly identify assets and their parameters, structure tags from enterprise historian or cloud data sources, and attach tags or other information, such as dashboards or knowledgebase links. Cloud connections: The new release also includes plug-and-play integration with Amazon and Microsoft cloud-data sources, such as AWS IoT SiteWise, Amazon Timestream, and Microsoft Azure Data Explorer. With these connectors, users can analyze time-series data with TrendMiner directly from cloud storage. Searches with insights: The feature offers visualizations of the distribution of durations, calculations, and other summary metrics via histograms. Users can interact with the histograms to select a subset of interesting events with respect to one or more summary metrics and subsequently explore the relation with other dimensions as the histograms dynamically update.
The TrendMiner 2023.R4 release introduces significant enhancements in reporting, connectivity and cloud support. It is aimed at accelerating IT/OT convergence and simplifying the integration of data sources. Enhanced data source connectivity: The release simplifies the process of connecting to ODBC and JDBC data sources, which allows easier access to various types of data. It democratizes data for operational experts, provides a more comprehensive view of operations, and aids in data-driven decision-making. Schedule manager: This allows for more tailored reporting experiences.
MLHub is a new module designed to bridge the gap between central data teams and operational experts. With MLHub, operational experts and data scientists are empowered to collaborate on a machine learning exercise. MLHub enables the creation, training, and deployment of machine learning models for deeper operational insights. · Enhanced Machine Learning Capabilities: MLHub allows data scientists to import data from TrendHub and ContextHub views, validate hypotheses using Python code, and deploy machine learning models.
TrendMiner offers greater flexibility in dashboarding and reporting features for even more insights on operational events in 2023.R2 including: Enhanced dashboarding and reporting: Get improved flexibility in dashboarding and reporting. Users can quickly identify process events and align them with specific results for faster, more efficient reporting across various views and assets. Conditional formatting: Operational events can now be formatted in tables within ContextHub. This allows users to immediately notice when parameters exceed predefined limits. Greater control over reporting timeframes: Engineers have enhanced control over reporting timeframes, facilitating more effective data access and analysis from multiple sources. Integration with AspenTech APRM: The integration allows for the visualization and improvement of batch process data from AspenTech’s Aspen Production Record Manager (APRM). Quick identification of outliers: ContextHub now allows individual or dependent column formatting, which allows engineers to quickly identify event types through color-coded cells in table view. Flexible data source connectivity: The new release includes a Generic Java Database Connectivity (JDBC) provider for data transfer from any source supporting a JDBC connection.