Industrial Data Lake
An industrial data lake is a data repository, similar to data lakes used in other types of organizations. In contrast to a data warehouse or other data storage options, industrial data lakes can hold enormous amounts of data in its native, raw format, which means it can store both structured and unstructured data.
Industrial data lakes are optimized for scaling to terabytes and petabytes of data, making it accessible to analytics tools that use machine learning (ML) to deliver deeper insights in real time. In process manufacturing, data is the key enabler to digital transformation and Industry 4.0. An industrial data lake can be used to realize a single view of operations and derive operational insights. These insights can be used to improve production quality, make real-time predictions, and generate cost savings.
Why is an Industrial Data Lake Important for Process Manufacturing Plants?
Process manufacturing organizations produce a vast volume of data on a constant basis. Until recently, this data mostly went unused, but today’s advanced AI and ML analytics can analyze it to generate valuable real-time insights, support process improvements, enable predictive maintenance, and much more.
Data lakes gather this data in a single location, regardless of where it originates. It can handle data in different formats and from different sources, ensuring that no data siloes or blind spots arise. With an industrial data lake, advanced analytics can access all the data, providing a full picture of plant and business operations.
In process manufacturing, an industrial data lake can provide new capabilities related to measuring performance, maintenance, and other areas of production. This can help manufacturers to make more informed decisions, reduce downtime, and increase efficiency.
How Should Process Plants Implement an Industrial Data Lake?
Refine your data governance
An industrial data lake is only effective when it’s supported by carefully thought-out data governance protocols. Decide which data will be imported into the data lake, and ways to catalog the data so you can find it again. Without data governance, data lakes can become data swamps, where data stagnates without delivering any value.
Future proof your data system
Data and data management is constantly changing and evolving. It’s hard to predict what the future will bring, so make sure your data lake and other parts of your data system can scale easily to accommodate greater volumes of data in the future.
Ensure your data lake integrates with your data system
Your data lake is a means to an end, namely Industry 4.0 and digital transformation. As such, it’s part of a wider data system that includes existing data pipelines as well as new data analytics tools. Think about the main use cases for your data and which tools you’ll be using to achieve those goals, and check that your chosen data lake setup integrates smoothly with all the relevant components.
Train your data managers
A data lake is a powerful tool, but like all powerful tools, it can only produce the desired results when it’s applied in the right way. Before you introduce a data lake, make sure that you have the requisite skills among your employees. You might need to hire new data science talent, or upskill existing employees to fill this role. At the same time, you’ll need to educate all your employees to understand and take seriously the insights generated through the data lake.
How Do Process Plants Benefit from an Industrial Data Lake?
An industrial data lake can help process manufacturers to realize a single view of operations and derive operational insights. It can provide new capabilities related to measuring performance, maintenance, and other areas of production, which can help process manufacturing companies to make more informed decisions, reduce downtime, and increase efficiency, ultimately impacting on the bottom line.
