Data Sources

Overview

Bazefield BI Data Sources are the foundation of all dashboards, reports, and analytics within the Bazefield Business Intelligence (BI) platform.  A Data Source represents a gold layer — a centralized, business-defined view of the core data required for asset monitoring, analytics, and especially reporting.

These Data Sources unify real-time, historical, and contextual information from the Bazefield Data Engine into curated, reusable datasets that can be shared across all BI Apps in an installation.

Training Material

This article covers the core concept and features of a data source.  Please continue to our Training Section if you’re ready to create your first BI Data Source for consumption.

Purpose

Data Sources act as centralized sources of truth, ensuring that all dashboards, reports, and analytical workflows across the enterprise reference consistent data and calculations. In practice, a Data Source is a curated collection of related time-series data points — typically grouped to serve a specific operational or analytical purpose, such as daily production reporting, year-to-date performance tracking, or real-time monitoring.

Conceptually, Data Sources are similar to global Point Templates installed on Asset Models, which define standardized signal configurations at the asset model level. However, while Point Templates form part of the unified, single global data model and any modification affects the entire installation, Data Sources introduce an additional layer of flexibility. They allow users to perform personalized modeling and on-the-fly business calculations without altering the core system configuration.

Because Point Templates are foundational and shared system-wide, they are typically restricted from direct editing by end users by Bazefield administrators. Data Sources, on the other hand, provide a safe, fully customizable workspace for business and analytical users to explore, combine, and extend data — enabling innovation and tailored KPI development without risk to the production environment.

Data Sources (compared to point templates) offer additional advantages, such as:

• Maintaining version-controlled, standardized datasets.

• On-the-fly simple business calculations from other fields in the data set

Primary Data Source Types

There are 3 currently supported data source types as of Bazefield 11.5.  Future releases (Bazefield 12 and beyond) will support additional sources of data involving events, allocations, cases, and work orders.

Points

Point Data sources represent a logical business grouping of time-series data, often aggregated at the same base interval (e.g. 1 hour, 1 day, 5 minutes, etc) for one distinct Asset Type.  It would be common, for example to place all daily required inverter reporting KPIs in one single data source and use it across one or more BI apps.    Beyond just specifying the exact point desired, users can also define:

Data Name:  Display alias for the point/calculation as displayed in the BI app.  

Time Period Aggregate:  Default time-series aggregation rule when a widget queries the point

Multi-asset Aggregation:  Default rule for how the data point aggregates when multiple assets are combined in one total (e.g. I want to “average” all my Phase A current’s across my inverters in the widget).  

Business Calculations

Users are not restricted solely to global points when selecting their data sources; they can also utilize straightforward algebraic expressions for real-time business calculations. These differ from conventional calculated points within an asset model, as they do not necessitate storage, are generated during runtime, and are specific to the Bazefield BI applications. In summary, they provide benefits in terms of configuration speed and adaptability, with the limitation that they cannot be utilized outside the Bazefield BI environment for other functions within the web portal.  

Calculations can be made to combine multiple points or attributes in a single expression, below an example of deriving a simple capacity factor expression by dividing the actual AC power by the nominal AC rated power and multiplying by 100.  

Availability Statistics

The Availability Statistics data source type provides a structured and efficient way to analyze custom rollups of the key bazefield allocation properties within a larger time period.  They leverage the daily rollups of the aggregation properties stored on every allocation in the Bazefield platform — allowing for high-performance daily and interval-based rollups without the need for raw event-level calculations.

Daily Resolution or higher

Custom availability statistics metrics in a BI data source are available at a resolution of one day or larger.  Every day, the Bazefield allocation service pre-aggregates all allocation properties per day per asset, and the availability statistics data source utilizes this data instead of the detailed allocation by allocation properties.  This offers much faster query performance during reporting.

Specifically, each allocation in Bazefield contains pre-aggregated metrics such as lost production, theoretical production, actual production, and duration (hrs) which can be accessed directly through Availability Statistics Data Sources.

Example use cases

There are several reporting use cases for availability statistics data in a Bazefield BI app; 3 simple ones displayed in this section.

Creating a metric in a BI app to display the sum of lost production in 3 IEC-61400 allocation categories.

Creating a custom revenue generation metric only during periods of full or partial performance operation on an asset

Creating a custom production based availability metric to display a custom availability % based on numerator and denominator totals of chosen categories within an allocation type.

Static Attributes

Static Attributes are especially useful in Bazefield BI Apps for enhancing reports with clear, contextual information about each asset. They provide simple but essential metadata — such as asset name, capacity, location, or model — that helps describe what the data represents. In many cases, Static Attributes are used purely for display purposes in dashboards or reports, allowing users to include descriptive details about assets alongside performance or availability metrics without needing to query external systems.  

Static attributes (numeric ones) also have significant value in creating simple business calculations as evidenced in the Points Data Source Type.  

Example Configuration of Data Source Types

To create a simple “Solar Site Production Overview” App, an end user might end up making 3 data sources:

• Points for irradiance, inverter efficiency, and energy yield,

• Availability Statistics for downtime events and lost energy,

• Static Attributes for site location, module technology, and owner.

These 3 data sources can then feed that single app, or be re-used and shared across other analytics dashboards or reports.

Product Certified Data Sources

Product Certified Data Sources are pre-shipped, validated datasets developed by the Bazefield Product Team.  They serve as the baseline analytical layer for Product Certified Apps, ensuring a consistent foundation across installations.  They are denoted by a green “product certified” shield in the BI Manager.  

Key principles of product-certified data sources:

• Immutable core definitions: Certified Data Sources cannot be modified, preserving product integrity.

• Clone and extend flexibility: Users can safely clone Certified Data Sources and append new fields, business logic, or calculations — creating local variants without altering the shared configuration.

• Empowerment without risk: This allows customers to innovate within their own installations while maintaining the global structure supported by Bazefield.

Usage Across BI Apps

Once published, Data Sources can be used across all Bazefield BI Apps within the same installation.  Multiple Data Sources can be combined in a single dashboard — for example:

• Overlaying Points (performance data) with Availability Statistics,

• Enriching with Static Attributes such as turbine type, manufacturer, or region,

• Or building upon a Product Certified Data Source for custom analytics.

When a shared Data Source is updated and republished, all BI Apps linked to it are automatically aligned — ensuring consistent business logic and values across the enterprise.