15 docs tagged with "interfaces"

Learn how to configure advanced settings in Visual KPI Designer, including interfaces, custom attributes, language options, navigation bar links, site rollups, and comment codes.

Explore the available interfaces in the Transpara system, including their use cases and how they enable data integration from various sources for Visual KPI.

Learn how to set up and configure interfaces in Visual KPI Server Manager, including prerequisites, installation steps, connection verification, and troubleshooting.

Learn the foundational concepts of Transpara Visual KPI, including KPIs, hierarchy and groups, design and authoring, data sources, interfaces, and access levels. These concepts provide the essential knowledge needed to master the system and optimize performance monitoring and decision-making.

Understand the core concepts of Visual KPI interfaces, including their components, configuration, security practices, and how they enable data integration and visualization.

Discover how Interfaces in Visual KPI connect and adapt data from various external sources. Learn about their components, purpose, and integration process to standardize and make real-time data available for KPI monitoring.

Learn how Visual KPI interfaces enable data integration from various external sources, including industrial historians, databases, REST APIs, and more.

Learn how to configure a JSON interface for integrating RESTful APIs with Visual KPI, including security settings, data paths, and parameterization for trend and historical data.

Learn how to configure an ODBC interface for integrating SQL databases with Visual KPI, including query creation, parameterization, trend and historical data, and aggregation settings.

Learn how to parameterize Visual KPI interfaces, including ODBC and JSON interfaces, to enable dynamic querying of data using placeholders and configurable parameters.

Learn how to configure Python interfaces for Visual KPI to retrieve and process data from any source, including examples of required methods for trends, historical values, and more.

Query-based charts in Visual KPI provide a powerful way to visualize data directly from databases using SQL queries. These charts support advanced configurations like ranged-based, stacked, and clustered visualizations for various data insights.

Explore the supported data sources for Visual KPI, including industrial historians, relational databases, web services, manually entered data, business applications, and IoT devices.

Learn how to install and configure the Transpara tStore interface, retrieve metrics and lookups, and use parameters like filters, aggregation functions, and buckets in Visual KPI.

Discover how to configure and parameterize Visual KPI interfaces, including ODBC, JSON, Python, and tStore, for seamless data integration and enhanced flexibility.