Benefits of a Modern Data Historian

Benefits of a Modern Data Historian | SPONSORED

Introduction

Industry 3.0 was all about automating processes using the computational power available to us. Industry 4.0 has taken it up a notch by deploying processes to judiciously use the enormous amount of data and derive valuable insights from it. Historical data plays a crucial role in enhancing process efficiency, forecasting equipment failures, monitoring energy consumption, and ensuring regulatory compliance. This brings to light something called data historians, which we’ll explore in this post.

A data historian is a specialized database that collects and stores time-series data from industrial processes, enabling detailed analysis and optimization.

What is a data historian?

A data historian is a specialized database that collects and stores time series data from industrial processes, enabling detailed analysis and optimization. It functions similarly to a time series database (TSDB), which is optimized for handling data points indexed in time order. In Industry 3.0, data historians primarily managed data from isolated sources like programmable logic controllers (PLCs) and supervisory control and data acquisition (SCADA) systems, focusing on basic historical analysis and troubleshooting within localized environments.

With Industry 4.0, data historians have advanced significantly. They now pull in data from IoT devices and cloud platforms, handling larger and more complex datasets. Modern historians use AI and real-time analytics to optimize operations across entire businesses, making them more scalable, secure, and integrated with other digital systems, perfectly fitting the connected nature of today’s industries.

Traditional Data Historian vs. Modern Data Historian

Traditional data historians were limited in scalability and integration capabilities, often relying on manual processes and statistical methods of data collection and storage. Modern data historians, particularly those built using a time series database (TSDB), offer significant improvements in speed and ease of data processing and aggregation. One such foundation for a modern data historian is InfluxDB.

Key components of a modern data historian

InfluxDB supports the modern data historian through efficient data collection, storage, processing, aggregation capabilities, and unlimited cardinality. Let’s delve into some key components of a modern data historian.

Data Collection

Real-time data collection is crucial for timely decision-making and operational efficiency. InfluxDB supports this by providing seamless data ingestion from diverse sources, making it versatile for many applications. It handles IoT devices, sensors, application metrics, log data, industrial control systems like SCADA and PLCs, and telemetry data from satellites, vehicles, and other remote sensing technologies. Additionally, it supports several types of data ingestion—real time, batch, or lambda-based systems. To efficiently ingest various forms of data, InfluxDB offers several tools for data collection: a server agent called Telegraf, language and platform-specific client libraries, direct integration APIs, and a scraping tool.

Data Storage

Modern devices produce high-granularity and high-volume datasets, also known as high cardinality, that general-purpose databases can’t handle well. A time series database (TSDB) handles time-stamped data, capturing changes over time. This design is crucial for monitoring and analyzing trends in real time. By monitoring real-time data, we can use real-time analytics for faster decision-making. We can also streamline customer experience by providing options that resonate with them. Additionally, real-time data can be used to analyze bottlenecks and improve overall efficiency. TSDBs associate a data point with a timestamp and create indices that allow quick retrieval based on time queries. They also have mechanisms to save this huge volume of data efficiently.

InfluxDB, a leading TSDB, efficiently stores and manages time-series data through its optimized storage engine, ensuring high compression rates and effective data retention policies. This allows for efficient storage and quick retrieval of vast amounts of data. InfluxDB’s scalability enables it to handle large volumes of data effortlessly. It supports horizontal scaling, allowing more nodes to manage increased loads, making it ideal for applications requiring extensive data collection in real time.

Data Processing and Aggregation

Processing and aggregating data is crucial for transforming raw data into meaningful insights, enabling businesses to make informed decisions. It also helps us address potential issues quicker, increase business efficiency, and optimize customer satisfaction. Real-time analytics,  made possible by real-time ingestion tools, offer significant benefits such as immediate anomaly detection, timely responses to operational changes, and proactive decision-making. InfluxDB’s real-time data processing and analytics ensure that the users can act on the most current information available, enhancing efficiency and performance.

Visualizing data is crucial for effective decision-making as it transforms complex datasets into intuitive, easily understandable formats.

Data Visualization

Visualizing data is crucial for effective decision-making as it transforms complex datasets into intuitive, easily understandable formats. This lets stakeholders quickly grasp trends, identify anomalies, and derive actionable insights. InfluxDB seamlessly integrates with visualization tools like Grafana, renowned for its powerful, interactive dashboards. Creating dashboards with Grafana involves a few simplified steps:

1. Connect to InfluxDB: Set up a data source in Grafana that’s linked to your InfluxDB instance.
2. Build Queries: Use Grafana’s interface to create queries that pull relevant data from InfluxDB.
3. Design Visuals: Choose from various chart types and configure them to display your data effectively.
4. Customize Dashboards: Arrange your visuals into a coherent layout, adding labels, legends, and interactive features for better clarity.

These tools and steps empower users to make data-driven decisions with real-time visual insights.

Data Accessibility

Ensuring data accessibility involves allowing different users to access and use the data they need efficiently. InfluxDB supports this by offering robust API capabilities that integrate well with other tools and applications. These capabilities allow users to access data programmatically and incorporate it into various workflows. InfluxDB’s APIs enable users to query, write, and manage data, facilitating interoperability with visualization tools, analytical platforms, and other systems.

Security is paramount in data accessibility. InfluxDB implements various security measures, including authentication, authorization, and encryption, to protect data integrity and privacy. User roles and permissions can be defined to control access levels, ensuring that only authorized personnel can view or modify sensitive data. Additionally, InfluxDB supports TLS/SSL encryption for data in transit, safeguarding against unauthorized access and ensuring data privacy.

Benefits of using InfluxDB for a modern data historian

Performance: InfluxDB 3.0 demonstrates high performance for real-time data, achieving 45x better write throughput and 2.5-45x faster query performance compared to its previous versions. This enables rapid data ingestion and efficient processing, which is critical for real-time monitoring and analytics.

Scalability: InfluxDB 3.0 scales horizontally, allowing it to handle large datasets without performance degradation. It supports the decoupling of compute and storage, enabling independent scaling of each component to meet growing data volumes and workloads.

Flexibility: InfluxDB integrates with many data sources and tools, including over 300 plugins and seamless compatibility with popular visualization tools like Grafana. This flexibility allows it to adapt to diverse data environments and workflows.

Cost-Effectiveness: InfluxDB 3.0 reduces storage costs by up to 90% through efficient storage compression and cost-effective object storage. It is a more economical choice than traditional systems, especially for large-scale time series data.

Getting started with InfluxDB

Basic Setup:

1. Sign Up: Begin by signing up for an InfluxDB Cloud account or downloading InfluxDB for local installation from the InfluxData website.
2. Install: Follow the simple installation process to set up InfluxDB on a machine or configure a cloud instance.
3. Create a Bucket: Next, set up a bucket to store the time series data.
4. Data Ingestion: Use Telegraf, InfluxDB’s data collection agent, to begin ingesting data from various sources like IoT devices, applications, or servers.

Resources:

• InfluxDB Website: Access detailed documentation, product information, and latest updates.
• Tutorials: Follow step-by-step tutorials to learn specific features and use cases.
• Community Forums: Join the community to ask questions, share experiences, and learn from other users.

You can explore InfluxDB’s features by experimenting with data queries and creating dashboards using Grafana or other compatible visualization tools. You can also refer to the provided resources to deepen your understanding and leverage InfluxDB’s full potential for your projects.

InfluxDB brings high performance for real-time data, scaling easily to handle large datasets.

Conclusion

InfluxDB brings high performance for real-time data, effortlessly scaling to handle large datasets. It integrates smoothly with various data sources and tools. Its efficient storage saves costs, which enhances operational efficiency. To reap these benefits, modernize your data infrastructure with InfluxDB. Sign up for InfluxDB Cloud or contact the sales team for a proof of concept.

As technology advances, effective data management becomes increasingly vital. InfluxDB helps businesses stay ahead, making data handling efficient and cost-effective. The future lies in transforming vast time series data into actionable insights, driving innovation and growth.