Flow Makes Industrial Data Management Easy

Effective Industrial Data Management (IDM) is crucial for optimizing operations, ensuring compliance, and driving intelligent decision-making. As manufacturers embrace Industry 4.0 best practices, they face a growing challenge: how to manage, contextualize, and utilize vast amounts of Operational Technology (OT) and Information Technology (IT) data in real time.

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The Growing Need for Industrial Data Management

The industrial sector generates massive amounts of raw data from sensors, machines, and enterprise systems. However, data silos, inconsistencies, and quality issues prevent organizations from harnessing this data effectively.

According to Verdantix's Green Quadrant, modern IDM software must offer:
  • Direct and Indirect Industrial Data Acquisition – Capturing data from various OT and IT sources.
  • Data Quality Management and Governance – Ensuring accuracy, consistency, and reliability.
  • Data Contextualization – Providing metadata and structuring information to make data actionable.

Flow Software delivers on all these requirements, with one crucial difference, that we are confident will drive Flow to the top of Verdantix's Green Quadrant for 2025. Unlike other solutions, Flow Software avoids duplicating data by linking to existing validated databases, extracting information only when needed.

Key Capabilities of Flow Software in Industrial Data Management

Flow Software’s comprehensive IDM suite is designed to meet the needs of modern manufacturers, asset managers, and industrial enterprises. Key features include:

1. Seamless OT/IT Data Integration

Flow enables manufacturers to integrate disparate data sources into a single source of truth. By leveraging standard protocols like MQTT, OPC, SQL, and REST APIs, Flow Software ensures seamless interoperability between SCADA systems, historians, ERP platforms, and cloud-based AI/ML applications.

2. Advanced Data Processing and Contextualization

Unlike conventional databases that simply store data, Flow Software applies real-time event processing and rule-based transformations to create actionable intelligence. Engineers and analysts can define custom calculations, aggregate data across time periods, and apply version-controlled transformations to ensure consistency across enterprise systems.

3. No Historian? No Problem

Flow’s Timebase Historian offers a modern alternative to legacy time-series databases. With a NoSQL binary architecture, it supports 25,000 updates per second, ensuring high-speed data capture and retrieval while maintaining a small storage footprint.

4. Industrial Data Governance and Quality Control

Data quality is a major challenge in industrial settings, where inconsistencies, missing values, and erroneous readings can impact decision-making. Flow Software implements automated validation rules, data lineage tracking, and governance frameworks, ensuring that only clean, accurate data is used in analytics and reporting.

5. AI-Ready Data Modeling and Analytics

Manufacturers leveraging AI and machine learning often struggle with unstructured, uncontextualized data. Flow Software simplifies AI adoption by structuring industrial data into an AI-ready format, complete with metadata, event-driven triggers, and domain-specific context. The platform integrates seamlessly with Snowflake, AWS, Azure, and Google Cloud, enabling advanced analytics and predictive maintenance applications.

Why Choose Flow Software for Industrial Data Management?

Flow Software stands out among IDM solutions due to its flexibility, scalability, and ease of deployment. Here’s why leading industrial firms choose Flow:

  • Unified Namespace (UNS) Integration: Flow aligns with Unified Namespace best practices, ensuring scalable data architectures that eliminate silos.
  • Low-Code/No-Code Configuration: Designed for both engineers and IT teams, Flow’s visual workflow engine minimizes development effort while maximizing customization.
  • Real-Time and Historical Insights: Organizations can track live data streams while also accessing historical trends for long-term optimization.
  • Edge-to-Cloud Compatibility: Whether deployed on-premise, at the edge, or in the cloud, Flow Software ensures seamless data accessibility across distributed environments.

Integrating a Unified Namespace Into Your Industrial Data Management Architecture

A Unified Namespace provides access to real time data, but does not address the need to query historic data or provide data transformations. In the video below, let's examine how the architectures that we have been using across industry have fallen short and how the UAF address these needs.

Isn't This Data Ops?

Unlike Industrial Data Management, which focuses on structured plant-level analysis, Industrial DataOps (IDO) ensures that real-time industrial data flows into higher-level IT systems for broader business insights and automation. IDO does not focus on historical analysis or structured data governance—instead, it ensures that data moves seamlessly between systems without delay, often serving as a pipeline betweenOT and IT environments.


Industrial Data Management

Industrial DataOps

Primary Purpose

Unifies, governs, and structures stored industrial data for analysis  and decision-making.

Moves real-time or event-driven data to higher-level IT systems, analytics platforms, and cloud applications.

Data Flow

Centralized; aggregates data from historians, MES, ERP, and quality  systems.

Distributed; event-driven data flow using real-time streaming.

Timing

Post-event; data is cleansed and structured after collection.

On-change; ensures minimal latency in data updates.

Integration

Provides structured data to BI tools, data lakes, and IT systems.

Enables seamless data movement between OT and IT.

Primary Users

Plant-level operations teams (process, maintenance, quality, production  engineers, and plant leadership).

IT teams, enterprise architects, and cloud infrastructure engineers.