Hey there,

Hope you are doing well. This week’s theme is about:

This is Part 2 of “The Digital Factory” series.

In Part 1 - The Digital Factory (Hub & Spoke) we covered and concluded:

In this Part we’ll briefly touch base on:

In future Part 3, we’ll cover, the reference architectures, the industry debates and few updates.

Ready? let’s dig in.

Yours truly.

— Yousuf.

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Its’ been a better start of the year - compared to 2024. The year has begun with doing few focused reviews / consulting / advisory across IT, OT and data privacy, in different manufacturing sectors and critical infrastructure org, so its been a very busy quarter. Interesting to note the similarities and differences in terms of asset owners approach towards cybersecurity.

In this edition, below, I cover a typical industrial data flow lifecycle, something that took me quite a while to uncover and wrap my head around in understanding the concept, so hoping it will save some good time for you.

To know more, please note that the digital factory series and few other previous ones are included as are part of IT-OT CySEAT Training - an upcoming offer. So if you have enjoyed, hope to see you on the wait-list, before its too late.

First lets look at what is Industrial DataOps, what stages of the maturity curve organisations go through and then understand a typical data flow iteration example.

Finally, we’ll look into some elements of securing this new industrial data.

DataOps is a set of practices that orchestrates people, processes, and technology to provide trusted, understandable, and ready-to-use data across the organization. In Industry 4.0, DataOps is crucial for managing the vast amounts of data generated by sensors and machines, ensuring data quality, and facilitating secure data flow3.

Digital manufacturers going through digital transformation, goes through following DataOps maturity curve.

To explain this, here’s an illustration to understand how physical machine data goes through few iteration cycle to become actional intelligence in digital world for the business.

The data flow can be divided into following stages as illustrated above:

Every stage and interaction point represents an opportunity, and as they say, where there’s an opportunity, there’s some elements of cyber risks that we need to cater.

At the connect and collect stage: we need to ensure using secure methods of connectivity and collection using secure protocols etc.

At the store, analyse and visualise stage: we are more concerned with data classification, governance, access controls and protections (at rest / motion).

At the finding data patters and reporting stage: we are still concern around same things as in previous stage, and in addition, cloud / AI security elements.

This is where/how OT data meets IT style data governance and security controls.

Ever wonder, why you keep hearing “IT and OT are converging….” ?

Though over rated and misinterpreted in most context, but gives you some ideas.

Consider a smart factory using IoT sensors to monitor production. Implementing DataOps involves:

Securing Industry 4.0 data lifecycle and implementing effective DataOps strategies are crucial for the success of digital factories. By integrating robust security frameworks and leveraging technologies like DLT and Data Fabric, organizations can protect their data while enhancing operational efficiency and decision-making capabilities.

Supporting Diagrams and Models

For a visual representation of the concepts discussed, consider the following models:

I’d love to know what have you seen works for:

If you’d like to learn more on this head to:

IT-OT CySEAT Training & join the wait-list soon, before its too late.

In 2024, Chief Information Security Officers (CISOs) have taken on a more strategic role in Operational Technology (OT) cybersecurity decision-making.

This shift is driven by their increased recognition as strategic leaders, aligning cybersecurity with business strategies and risk management.

CISOs are now more involved at the board level, with 30% sitting on corporate boards, enhancing their influence on cybersecurity investments and strategies.

Improved alignment with board members facilitates informed decision-making.

CISOs focus on quantifying cyber risks and bridging IT and OT security, ensuring comprehensive protection.

They also adopt advanced technologies like AI and ML for better threat detection and response.

Overall, CISOs' roles have evolved to encompass risk management, board engagement, and technological integration, highlighting the growing importance of cybersecurity in organizational leadership.

In case you’ve missed - here are some of my recent most viewed social posts.

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