Overview
Data Sources are the first configuration layer in BI Manager, enabling consistent and structured access to data for dashboards, reports, and applications. They define what data is available, how it’s aggregated, and how it’s used across the platform.
Definition
In Bazefield BI Manager, a Data Source is a configurable entity that defines how data is sourced, structured, and aggregated for use across dashboards, widgets, and reports. It establishes the relationship between a specific asset type and a selection of points or calculations, determining what data is made available for analysis. Each data source includes parameters such as the aggregation method (e.g., average, sum), time interval (e.g., hourly, daily), and the assets it applies to. Once configured and published, a data source acts as a reusable data layer that can be linked to one or more Applications. This ensures consistency in how data is interpreted and visualized throughout the BI Manager, supporting scalable and reliable analytics across the platform.
Data source types
The platform provides four distinct data source types, each designed to support different analytical use cases and visualization requirements. Understanding these data sources will help you choose the most appropriate option for your monitoring and analysis needs.
Aggregated Point Time Series
The Aggregated Point Time Series data source enables comprehensive time-based analysis by aggregating multiple time series within identical time intervals. This powerful data source applies various aggregation functions including average, sum, minimum, maximum, and other statistical operations to your data points.
Key Features:
Processes multiple time series simultaneously using consistent time-based aggregation
Generates separate aggregated time series for each selected point within a single asset type
Covers user-defined time ranges for flexible analysis periods (Use App time period toggle button)
Enables comparative trend analysis across multiple measurement points
Maintains temporal consistency across all aggregated data sets
Best Use Cases:
Comparing performance trends across multiple sensors or measurement points
Analyzing patterns in grouped data over time
Creating unified views of related time series data
Compatible Widgets: Timeseries, Heatmap, Asset Summarized Metric
Availability Statistic
The Availability Statistic data source focuses on operational performance metrics by calculating availability-related statistics for selected asset types over specified time periods. This data source consolidates complex availability calculations into single, actionable values.
Key Features:
Computes comprehensive availability metrics including lost production and actual production values
Delivers single-value statistics representing overall asset performance
Covers user-defined time ranges for flexible analysis periods (Use App time period toggle button)
Provides standardized availability calculations across different asset types
Best Use Cases:
Tracking operational performance and uptime metrics
Identifying availability patterns and performance bottlenecks
Generating executive-level performance summaries
Supporting maintenance planning and resource allocation decisions
Compatible Widgets: Asset Summarized Metrics, Asset Metric Chart, Report Writer, Heatmap
Real Time Point Values
The Real Time Point Values data source provides immediate access to the most current measurements from your connected systems. This data source prioritizes real-time visibility over historical analysis, making it ideal for active monitoring scenarios.
Key Features:
Retrieves the latest available values from one or multiple measurement points
Operates independently of historical data dependencies
Provides immediate data refresh capabilities
Supports simultaneous monitoring of multiple real-time data streams
Best Use Cases:
Live monitoring dashboards and control room displays
Real-time alert systems and threshold monitoring
Current status verification and system health checks
Operational decision-making requiring immediate data
Compatible Widgets: Asset Summarized Metrics, Asset Metric Chart
Single Aggregated Point Values
The Single Aggregated Point Values data source applies mathematical aggregation functions to historical time series data over defined time ranges, returning consolidated single values for each selected point. This data source transforms time series data into summary statistics for simplified analysis and reporting.
Key Features:
Applies comprehensive aggregation functions including average, sum, minimum, maximum, and advanced statistical operations
Processes data over user-defined time ranges with flexible period selection
Generates individual aggregated values for each selected measurement point
Supports complex statistical analysis and summary reporting requirements
Best Use Cases:
Calculating summary metrics such as total production volumes or average operating temperatures
Generating periodic performance reports and KPI calculations
Covers user-defined time ranges for flexible analysis periods (Use App time period toggle button)
Compatible Widgets: Analytics Map, Asset Summarized Metrics, Asset Metric Chart
Attribute Configuration
All data sources support attribute configuration, enabling you to add supplementary data fields beyond the primary measurement points. The system supports numeric attributes with multi-asset aggregation capabilities, allowing you to combine values across multiple assets using various aggregation functions. Use the "Add Attribute" button to create new attributes and organize them alongside your configured points for enhanced data analysis and reporting.
Calculation Configuration
Single Aggregated Point Values Data sources support custom calculations that enable you to create derived metrics using mathematical expressions. Calculations are configured with a unique name and an expression that defines the mathematical operation to be performed on your data points and attributes.
The expression field provides an intuitive interface for building mathematical formulas using your configured points and attributes.
The calculation engine supports a comprehensive set of mathematical operators:
Addition (+): Combine values (example: a + b)
Subtraction (-): Find differences between values (example: a - b)
Multiplication (*): Calculate products (example: a * b)
Division (/): Compute ratios and rates (example: a / b)
Modulo (%): Find remainders from division operations (example: a % b)
Selecting the Right Data Source
When choosing a data source for your analysis, consider these factors:
Time Sensitivity: Use Real Time Point Values for immediate monitoring, or time series options for historical analysis
Data Complexity: Choose aggregated options when you need to consolidate multiple data points or time periods
Output Requirements: Select single-value sources for summary metrics, or time series sources for trend analysis
Widget Compatibility: Ensure your chosen data source supports your preferred visualization widgets
Each data source integrates seamlessly with its compatible widgets to provide comprehensive analytical capabilities tailored to your specific monitoring and reporting requirements.