Top 5 Criteria for Operational Time-Series Database Selection

Companies are transforming operations and manufacturing using new time-series database technologies for the IIoT and the digital transformation. Traditional operational historians and time-series databases are changing and adapting to address the digital transformation.  The new generation operational historian or industrial data platform is an industrial time-series database used to capture and transform time series data into operational visualization to support industrial operations analysis and decision-making and the digital transformation.  The next gen historian is more than just a platform for data storage.  Platforms for the today’s time-series databases should include on-premise, edge and cloud, etc.

The modern historian, industrial data platform and time-series database should connect to data easily, clean and validate data, analyzes and visualize the data and ensure data quality.  There are many strategies, features and capabilities users should consider when selecting a new operational time-series database today, that should align with data needs and uses and with the business’ IIoT strategy.   For example, companies need to use a time-series database that is more asset-based so that it is easier to search for specific information in real-time.  Specific production reports and other data tools specific to the application or industry should also be considered.   The databases should also be able to easily connect with other types of unstructured data such as video, weather and more.

Real Time-Series Database Strategies

Below are a few strategies and capabilities companies should consider when updating or acquiring a process historian. 

1. Become a data driven culture and eliminate data silos.  Although this may seem obvious to some companies – it may be difficult to implement because of a “knowledge is the power” culture that exists in some organizations today. 
2. Start to invest in new modern data platforms with features that accommodate your organization’s data needs including the ability to connect to other unstructured data types like weather, video and more.
3. Start to invest in new databases and management tools; use tools that contextualize, ensures data quality.  Tools like asset model tools and other advanced tools such as analytics should be considered.
4. Consider and use new visualization tools and digital dashboards that enable workers to get intelligence faster for data-driven decisions.
5. Begin or continue the digital transformation by moving data to public or private clouds, or data lakes.  Accommodate process requirements as necessary and keep some data on-premise or in the edge of in a private or public cloud, or even a data lake.

These are just a few of the strategies companies should consider when deploying operational historians/ industrial data platforms for data collection, storage, analysis and visualization – most of which they are already collecting. 

Operational Historian Time-Series Features for Selection

There’s a lot of value in the data and companies must continue to extract the value from their data.  To learn more about what others are doing with their process data including the leading suppliers and rising stars, some key data considerations, and strategies for the next gen process historian or industrial data platform, ARC has produced a new Operational Historian/Industrial Data Platform Market Analysis report and Supplier Selection Guide for both the process and discrete industries. Extract the value from your plant and operations data by investing wisely in new operational historians, real-time databases and other data analysis solutions.