Unified Namespace and InfluxDB: Streamlining IIoT Operations for Industry 4.0

Unified Namespace and InfluxDB: Streamlining IIoT Operations for Industry 4.0 | SPONSORED

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The Industrial Internet of Things (IIoT) has revolutionized the way industries operate, enabling businesses to collect and analyze data from their operations in real-time. However, managing and analyzing data from diverse sources can be a challenge. While sensors and systems may use the same transport protocols, the shape and type of data generated can vary from one device to another. A lack of uniform, clean data creates challenges and obstacles when it comes to getting timely insights. This is where a unified namespace and InfluxDB come into play. 

We’ll look at how a unified namespace can simplify data management, ensure seamless data flow, provide flexible data storage, and enable robust data visualization for IIoT operations, ultimately leading to improved efficiency, productivity, and profitability in Industry 4.0.

The power of a unified namespace: simplifying data management

Data is the lifeblood of industrial operations in Industry 4.0. A unified namespace offers a single, consistent way to organize and access data from various devices, sensors, and systems. As systems become increasingly complex and data silos become a greater impediment to progress, a unified namespace acts as a centralized data hub.

A time series database, like InfluxDB, is an ideal option for this data management layer because it can handle data collection and storage in a single place. Designed for unique time series workloads at any scale, InfluxDB eliminates the need for complex data transformations and mappings. It also saves time and resources and enables seamless data integration from different sources, making interoperability and collaboration across the entire industrial ecosystem easier.

A unified namespace also provides additional administrative advantages. For example, it can enhance data security and privacy by centralizing access control and governance. This means you can maintain strict control over who has access to sensitive data, minimizing the risk of unauthorized use or breaches.

It also provides the opportunity for more holistic data analysis and reporting. Storing all your data in a single data store enables unified views of data from multiple sources. This allows you to make connections and glean insights that would otherwise be inaccessible with fragmented and siloed data. As organizations strive to be data-driven, a unified namespace makes it easier to extract insights, identify trends, and make informed decisions that drive operational efficiency, productivity, and profitability.

Real-time data ingestion: ensuring seamless data flow

Real-time data ingestion is crucial for collecting data at the same speed that industrial sources generate it. 

For applications that generate large volumes of data, such as sensor networks or IoT devices, Telegraf is a powerful tool for real-time data ingestion. Telegraf is a lightweight data collection agent that collects data from various sources. It can process that data and then output it to any desired data store, like InfluxDB. It has over 300 plugins, so it’s capable of handling virtually any type of data. Plus, it’s open source, so you can write your own custom plugins too. (Check out Telegraf Basics at InfluxDB University for more info on that.) But plugins for common IIoT/OT protocols already exist, e.g., MQTT, ModBus, OPC-UA, and more.

InfluxDB also supports client libraries in multiple languages to ingest ‌data directly into the database. So regardless of what you have generating data or how you want to transport it to your unified namespace data store, InfluxDB has a solution. Regardless of how you get it there, InfluxDB can ingest that data in real-time.

Flexible data storage: adapting to diverse industrial needs

Recency bias tends to be strong with time series data. As it ages, it becomes less useful, and some businesses purge it. However, the increasing desire to implement machine learning and predictive processes (e.g., analytics, maintenance, etc.) requires high-resolution, historical data. 

This means that industrial operators that are leaning into digital transformation and evolving into an Industry 4.0 context need to factor data storage into their plans. Here, again, we see the benefit of a unified namespace architecture with a database like InfluxDB. 

For short-term storage, you can utilize single-node edge instances. While these may have more limited resources compared to a central hub, they’re great for users at the edge who need that data locally for critical decisions and insights. You can then send that data to ‌a centralized instance using the edge data replication (EDR) feature. The nice thing here is that everything plays nicely together, and you only need to keep the most important data at the edge.

Having a central hub for storage and data analysis allows you to take advantage of InfluxDB’s data compression capabilities. First, the architecture of the database itself (a columnar data store) enables it to compress data efficiently. Second, it uses Apache Parquet as its persistence format, which also has high compression ratios and further compresses the data. So, you ultimately save more data in less space. The final element here is saving those Parquet files on low-cost object storage, which can save 90% or more on storage costs. 

Organizations no longer need to compromise between getting deep insights and storage costs.

Robust data visualization: gaining insights from industrial data

Data analysis and visualization enable businesses to unlock valuable insights from their industrial data. By transforming raw data into visual representations, organizations can gain a deeper understanding of their operations, identify trends and patterns, and make data-driven decisions that drive success.

When it comes to data visualization, InfluxDB leans on integrations with best-in-breed solutions. The combination of Telegraf, InfluxDB, and Grafana is known as the TIG stack. Grafana is an open source data visualization tool with a native InfluxDB integration. InfluxDB also supports tools like Tableau and Apache Superset for data visualization.

Using InfluxDB as the backbone of your unified namespace approach means that you can use your data visualization tool of choice to power real-time data queries. Because all your data is in a single data store, you can query across dimensions and generate insights otherwise unavailable with legacy data historians and siloed data stores. The result is a holistic view of industrial operations and the ability to correlate optimizations and efficiencies across different areas of production to improve overall output.

InfluxDB also supports the integration of machine learning algorithms, allowing businesses to leverage advanced analytics for predictive maintenance, anomaly detection, and root-cause analysis. By applying machine learning techniques to industrial data, organizations can identify potential issues before they occur, minimize downtime, and ensure uninterrupted operations.

Next steps

The evolution to Industry 4.0 capabilities does not happen overnight. Industrial operators with large distributed systems that want to optimize productivity across their operations should consider the benefits that a unified namespace provides. Not only does it simplify data management by normalizing data from an array of sources, but once that data exists in a database, you can use and extend it in new ways because of the capabilities of a datastore like InfluxDB. At a time where real-time data collection and queries matter for large workloads of high-resolution data, a unified namespace can enable efficiencies and optimizations that give you a leg up on the competition.

About the author

This article was written by Jason Myers. He is currently a Content Marketing Manager at InfluxData. He earned a PhD in modern Irish history from Loyola University Chicago. Since then, he has used the writing skills he developed in his academic work to create content for a range of startup and technology companies.

 

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