From Manufacturing to oil and gas and even metals and mining, asset-intensive industries are not shy of data challenges. Here are three of the top issues that need to be addressed in these industries in 2025:
Data Quality and Silos: One of the primary challenges facing asset intensive industries is ensuring the quality and integrity of their data. Poor data quality, and dealing with silos, leads to inaccurate insights, operational inefficiencies, and downtime.
IT security: Historically, asset intensive industries also increasingly face challenges relative to the security and privacy of their data. With the rise of cyber threats and data breaches, organizations have had to invest in robust cybersecurity measures to protect sensitive information.
Real-time Data Access: Ensuring all parties have access to real-time operational data and subsequent context is key to better decision making in 2025.
Despite the first two issues, as asset intensive companies start to integrate new tools like AI and Digital Twins to drive business decisions, they also face a growing challenge of ensuring resources and teams like data scientists can access the same real-time data, with context, as engineers and operators.
Data scientists, especially in ICS or asset-intensive industries, face difficulties accessing critical information, especially when that data is contained in the tools and systems that engineers and operators typically employ. Additionally, the context supporting that data, as well as the large volume of it, can become an issue. Data scientists need to handle large volumes of data and interpret that data, often without the insights that engineers and operators have in the field.
Achieve Data Driven Success in 2025
Turning challenges into revenue and profit can be accomplished in 2025. There are several steps companies can take to improve data access, collection, and storage. With the increasing volume and complexity of data generated by assets, plants and factories must have systems and processes in place to accurately collect, store, and analyze this data. RADIX recommends a two-pronged approach:
Start with standardizing data collection processes, which includes developing guidelines for collecting data to ensure consistency and accuracy and other best practices to facilitate the analysis of data across diverse sources.
Invest in data processing tools and software to streamline the data cleaning, transformation, and analysis process is one of the first steps to mitigating the data collection challenge. These tools save time and improve the accuracy and reliability of the data while helping regulate data quality checks. Regularly monitoring and validating data quality is essential for identifying errors or inconsistencies. This can involve running automated checks, conducting manual reviews, or implementing data cleansing processes.
The issue with investing in data processing tools is attempting to choose the correct one that will quickly become the backbone of your company’s operations. Many tools come off the shelf completely bloated and bogged down with features you don’t need, and which are complicated to learn and use. They can add unnecessary complexity to your network while also failing to accomplish your key data integrity goals.
A purpose-built solution is required, which is why Radix created Leafcutter. The Leafcutter platform supports the needs of data scientists by allowing them to overcome the many challenges of gathering good, high-quality data from huge repositories. And it can do it quickly without adding bloated features or additional complexity to the operations. It works by streamlining the data management of the historian ecosystem for off-premises use, integrating seamlessly with cloud-based data lakes, real time analytics platforms, and ETL engines while boosting real-time analytics and reporting.
Leafcutter securely unlocks real-time data from siloed historians to deliver operational excellence, cost efficiencies and scalability. More than just a groundbreaking data streaming tool, Leafcutter is a meaningful change in the way it empowers asset-intensive industries to leverage their data and pair it with cloud analytics and other emerging technologies. It is a critical tool for turning data insights into operational excellence in a modern, complex, and data-rich environment.
Contact us today at Connect with us | Radix (radixeng.com) to try a free demo.
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