Augment, Democratize, Consumerize
The 2020s have been eventful for enterprises in the Kingdom of Saudi Arabia and the Middle East. Even the most conservative tech adopters were forced to take a digital leap that would have been unimaginable in the pre-pandemic era, and the results of the global digital-by-necessity experiment so far have been staggering.
Much has been written about tech in the workplace so, for this article, we are focusing on a very specific field of technology: industrial data management. More specifically, we are zooming in on how cloud data storage will finally be connected to industrial use-case solving at scale, unlocked by advances in that elusive-yet-critical “hidden layer” between data storage and application logic.
These are not more vague predictions about digital twins. In fact, we expect three bigger themes to dominate the sector this year:
- Augmentation – the process of enhancing or amplifying existing capabilities.
- Democratization – the widespread accessibility of data-driven insights to non-specialist users.
- Consumerization – ease of use, patterned after consumer applications.
These prevailing themes—augmentation, democratization and consumerization—are the foundation for industry 2.0. With that in mind, let’s explore the four significant trends that stand to redefine the data management landscape in the next couple of years.
1: A new era of data governance
First on our list, traditional corporate data governance will give way to a more democratized, ambient approach. Organizations will need to tailor their data governance strategies to suit different types of data and analytics, shifting from a centralized, use-case-agnostic practice to one that is deeply tied to the needs of actual data consumers and their data-driven use cases.
Through this paradigm shift, data governance—and master data management—will become a facilitator, rather than a hindrance, to faster use case execution and greater team autonomy. As a first step, we predict that data discovery will become an indistinguishable part of data governance.
2: Through AI, industrial data will learn to speak human
AI-driven active metadata creation permeates industrial data management, shifting the emphasis from data storage and cataloging to a true human data discovery experience. For application developers and data scientists, understanding—and handling—industrial data is not as straightforward as dealing with tabular data.
What’s even harder is understanding the context of industrial data—especially if you’re not a subject matter expert with years of intimate experience with the asset. Now, with AI making a steady march through industry, we expect to see technologies such as NLP, OCR, computer vision, trained ontologies and graph data models used to automatically contextualize ET/OT/IT, so the data is available for intuitive human use as well as programmatic discovery and analysis.
3. Enterprises will invest more in metadata (and its management) than in data (and its management) itself
When a data lake is not properly controlled, it becomes a data swamp . Currently, too many data science teams are scrambling to convert the contents of their data warehouses and data lakes into business value.
To meet the market’s growing need for human-understandable data, the role of metadata management is stepping up. This change is driven by the expansion of the Chief Data Officer’s mandate, which now includes metadata ownership, a responsibility previously held by the CIO.
4: DataOps will connect data managers to data consumers in real-time, at unprecedented scale
Data operations—DataOps—is collaborative data management for the AI era. The convergence of data management with data analytics continues to accelerate, driven by a surge in data literacy among data users. Seamless data operationalization across all workflow steps, ranging from data sources to live applications, becomes the new ‘data trapped in source system siloes’ challenge for digital and innovation leaders.
Stay ahead of the trend curve
CNTXT is your digital transformation partner in the MENA region. Through leading Google Cloud solutions, industrial software and digital know-how, we empower you to act on the industrial data trends to maximize your enterprise’s competitive advantage.
CNTXT can help you future-proof your data infrastructure, enabling you to contextualize your data so it’s ready for numerous AI applications and to capture the insights you need.
Together, we can unlock your enterprise’s limitless capacity for growth through digital transformation and data-driven insights. To book a consultation, please contact us.
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