The IT-OT convergence (part II): The Data Journey

This is the second article produced as part of a series where we will be covering the complexities of the Digital Transformation in industrial companies towards the full IT-OT convergence. This time we focus on the Data Journey


What do we mean with “Data Journey”?

As companies start their digital transformation process, they plan and implement a data-centric strategy. Their “Data team” explores how to leverage the company’s data to solve specific problems, optimize processes, or create new revenue streams. This is a journey that starts by obtaining data and can culminate as far as in the creation of AI models from this data. This is the Data Journey

This is the second article produced as part of a series where we will be covering the complexities of the Digital Transformation in industrial companies towards the full IT-OT convergence. Let’s get to it!

(If you haven’t read it, we suggest you start with the first article in the series. It will give you a nice overview of the whole Digital Transformation process)

The Data Journey: from Data to Insights

In the process of planning and implementing a data-centric strategy, companies start their journey by obtaining data and can culminate as far as in the creation of AI models from this data.

The Data team will typically spearhead these activities, focusing on specific problems or challenges according to the company’s needs. They will define a strategy that includes determining which data to collect and how to transform this data into actionable insights.

It all starts with the data.

Data teams will use company data to create their first "business intelligence" applications, such as visual dashboards to present information or generate reports. Depending on the strategy, it’s likely they will evolve these applications into more intelligent ones, based on Artificial Intelligence.

First challenges: gathering the data

Data teams will face this situation: they may not have access to the data they need to start implementing their strategy. It is quite usual that Data teams, specially when they have a clear AI focus, start experimenting with offline data (CSV files, Excel sheets…) that someone in the Operations or Infrastructure teams have handed to them.

But even with that, there will probably be some data they are not able to use because there is not yet a way to extract it or it’s not accessible easily. That will diminish the scope and ambition of the data-centric strategy. 

If the company wants to make the most of their digital transformation they will have to work on letting their Data Teams have access to that data by adding sensors (to measure some magnitudes that weren’t being measured) or connecting their industrial assets

Transforming data into information

Once data is gathered, the next step is transforming it into useful information. This phase is crucial because raw data alone doesn’t provide much value until it is processed and presented in a comprehensible format. The Data team will often create dashboards and reporting tools to visualize the data. These tools help stakeholders understand trends, identify anomalies, and make informed decisions.

Dashboards can display real-time metrics, offering a snapshot of operations at any given moment. Reports can be customized to provide alerts on specific conditions, helping teams react promptly to any issues. This transformation of data into information is the foundation of Business Intelligence applications, which are the first step towards more advanced analytics.

As these tools become more sophisticated, they can start incorporating predictive analytics, where historical data is used to predict future events. This can significantly enhance decision-making processes by anticipating potential problems and opportunities.

Reaching the maturity: Intelligent systems

The ultimate goal of the Data Journey is to develop intelligent systems that can automate decision-making processes and optimize operations in real-time. This is where AI and machine learning come into play. By leveraging advanced algorithms, companies can create systems that not only analyze data but also learn from it and make autonomous decisions.

Intelligent systems can predict equipment failures before they happen, schedule maintenance to minimize downtime, and optimize production processes for efficiency and cost savings. They can also adapt to changing conditions, improving their performance over time. This level of sophistication requires a robust infrastructure that can handle large volumes of data and perform complex computations at the edge.

Implementing intelligent systems also involves integrating IT and OT seamlessly. IT teams provide the computational power and data management capabilities, while OT teams ensure that the infrastructure is reliable and secure. Collaboration between these teams is essential to create a cohesive and effective intelligent system.

Companies that successfully implement these systems can achieve significant competitive advantages, including reduced operational costs, improved product quality, and increased agility in responding to market changes.

Barbara, a software for every step in your Data Journey

Data teams need tools to help them orchestrate all the applications and even AI algorithms that they will eventually deploy in distributed locations.

And Infrastructure teams need tools to help them transition their infrastructure from being isolated, to becoming truly intelligent.

This is exactly what Barbara does.

Barbara is software that empowers Data Teams to deploy, run, and monitor data-based applications and AI models on-site, simpler than the cloud, while providing OT teams the necessary tools to transform their infrastructure into an intelligent one.

We do this with an Edge infrastructure, enabling companies to overcome the costs, privacy and latency challenges that the Cloud presents.

The journey from data collection to the implementation of intelligent systems is complex, but it is essential for companies aiming to stay competitive in today’s digital age. By understanding and navigating each stage of the Data Journey, from initial data gathering to the deployment of AI-driven solutions, industrial companies can unlock significant value. With the right tools and a clear strategy, they can transform their operations, improve efficiency, and drive innovation. Barbara is here to support you every step of the way, ensuring your transition to an intelligent, data-driven enterprise is smooth and successful.

Want to keep abreast with Edge Computing? View our recent webinar about "How to Maximize yoru Edge Data: Transitioning from Connected Edge to an Intelligent Edge"

  • You will understand what drives successful Edge Computing deployments, and identify the right technology and platform.
  • You will discover how companies spanning the energy, manufacturing, and utilities industries have leveraged their own data to improve the performance of their operators and increase reliability.
  • You will explore each stage of a digital journey to build an intelligent edge and grasp the importance of addressing infrastructure requirements early on.