CDOs will already understand the nuances of those six areas in the context of their business. So rather than delve into them in detail, let’s instead acknowledge that any of these in isolation generate complexity through their diversity.
CDOs must contend with diversity of the data itself, the users they need to serve, the technologies involved, and the organizational boundaries they need to cross:
- Data: Quality, timeliness, format, structure, location, update frequency, governance, etc.
- Users: Data scientists, analysts, engineers, domain experts, business leaders, data product managers, legal, compliance, etc.
- Technology: Databases, source systems, file storage, cloud storage, data lakes, data warehouses, etc.
- Boundaries: Teams, departments, legal entities, jurisdictions, partners, customers, suppliers, etc.
Much of the focus for solving complexity has been placed on technology. The reality is that no single technology can service the diversity of data and users at play or effectively transcend organizational boundaries. Perversely, efforts to remove complexity have resulted in further compounding the issue. The primary example of this has been the push towards data centralization. This approach has been criticized for offering a solution aligned to — and dependent on — a specific technology provider. It’s also incredibly expensive.
More recently, federated and decentralized data architectures like data fabric and data mesh have gained support in trying to address complexity rather than remove it. However, these approaches have been criticized for lacking tangible recommendations, leaving much to the would-be implementer to navigate and solve. Additionally, much of the technology that would be required to make that a reality at scale, and across complex environments, is nascent and continues to evolve. Consequently, most organizations already have a hybrid architecture and will continue to have one regardless of their current preference.
Let’s start by exploring the challenges created by the diversity of data, users, technology, and organizational boundaries and considering some practical solutions…
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