Software Toolbox Technical Blog

With the advent of cloud-based solutions in every industry, it's only natural that you might need to migrate from a traditional locally-hosted SQL database for logging your process data to Azure. Fortunately, logging both to traditional SQL and Azure SQL are similar in many ways and OPC Data Logger makes it possible to log to both for OPC UA and DA data sources.

In this video blog, we'll review the basic setup and architecture for OPC Data Logger and then step through the configuration required for logging to SQL and Azure SQL from an OPC server.

At Software Toolbox, we commonly hear from users seeking a solution for connecting and gathering data from this or that type of hardware.  Beyond that, though, is what users do with the data once they have it.  A common need is reliably logging process to a database such as Microsoft SQL server.

In this blog post, we’ll discuss a specific use case of a German R&D firm needing to collect data from multiple OPC data sources and log that data to a SQL database for further analysis geared towards a pilot project developing a model for optimizing Combined Heat & Power Partnership (CHP) technology for transferability to many enterprises where heat and power generation are essential to the process.

With the relatively recent availability of OPC UA server capabilities in Siemens S7-1500 PLCs, access to live production data is now open to third-party applications. As a result, those applications can now communicate with hardware that was formerly locked behind proprietary communication drivers.

The OPC Data Logger's OPC UA client interface allows users to quickly and easily connect to S7-1500 PLC’s and log data to their preferred data storage option without the need for intermediate applications. This blog post covers the high-level steps involved with logging data from an S7-1500 controller and you can then download the free hands-on guide with detailed steps.

As you are probably aware, OPC Data Logger is an OPC lab-certified solution for dynamic, event driven logging of process data to standard SQL/ODBC databases, including Microsoft Azure SQL, or text/CSV files.  As part of the continuous improvements process for OPC Data Logger, we have regular product releases that provide updates to existing features and new functionality.

In this blog post, I'll cover some flexible new features that you may not be aware of from our most recent releases of the OPC Data Logger available now in V3.7.0.1.

As you may be aware, OPC Data Logger is an OPC lab-certified solution for dynamic, event driven logging of process data to standard SQL/ODBC databases, including Microsoft Azure SQL, or text/CSV files.  The wizard-based interface provides easy, flexible configuration that easily scales for project both large and small.

In this blog post, I'll cover some exciting new features that you may not be aware of from recent releases that are available in the current version.

What is the most important feature for any data logger to have? At the end of the day, we are trusting a data logger to take our data and store it.  Now whether that is for reporting, optimization, legal reasons, or simply to retain process data over some period of time in case it might be needed later, we expect the data to be logged without any losses.

This is particularly true in the industrial automation space, where the amount of data that is being logged is growing almost as exponentially as the speed at which the data is needed in order to have a business impact. As such, the prospect of losing data can very quickly result in lost jobs, thousands of dollars in lost production, and legal or financial penalties in case of an audit.

So how much do you trust your data logger to really be logging 100% of the data that it should be? In this blog post, I will address these concerns and highlight the ways OPC UA provides capabilities that software applications can leverage to provide peace of mind.

Does your data logging software force you to define the location where you're logging your data ahead of time?  Wouldn’t it be nice if your logging software could evaluate your data and make a decision on where the data should be logged?

In this first of two posts in a series on dynamic SQL logging, I'll show you how the OPC Data Logger can easily be configured to switch between SQL Tables at runtime, reducing any post-log sorting you have to do in SQL and saving you time and effort in the process.

Do you need to log specific process data to a database or text file based on some predefined variable or condition? We typically refer to this concept as "conditional" or "condition-based" logging.  It sounds simple enough but without a plan, it can be a tricky task to implement.

In this post, I'll introduce you to the considerations involved with conditional data logging and cover how OPC Data Logger can easily be set up to log data based on a variety of conditions without a lot of headaches.