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Data Fabric and Innovating at the Semantic Layer

The concept of data fabric has come a long way. Today, tooling can provide you inputs that seamlessly integrate, manage, and access data from diverse sources across the enterprise. With multi-structured datasets becoming the norm, it provides a far easier access layer for absorption of the datasets into the enterprise data memory layer which includes the archival of the sets.

This can potentially help with:

• Simplification and standardization of the data ingest processes
• Enabling a better integrated view of the data across the enterprise, especially for consumption
• Responsiveness of addressing business needs
• Can work as a layer after a multi-structured and/or distributed Data Vault solution

Add to this the innovations that are happening at the semantic layer, which essentially translates a business conceptual model interface into accessible data sets, and you have a winner by:

• Enabling a consistent business vocabulary across the organization
• Creating a business access layer from the Data Vault areas while not compromising on the ingest, integration and archival capabilities.
• Providing a more robust foundation for managed self-service analytics
• Including data and pattern discovery across the enterprise

The Data Vault 2.0 solution is already the most complete system for building out any analytics solution which works across people, process, and technology. Incorporating Data Fabric and the Semantic Layer can enhance it even more while continuing to leverage its robustness and completeness, making your data strategy more comprehensive and sustainable.

Data Vault and Data Mesh

Data Mesh as a concept is now generally accepted; however, it still lacks a set of exact steps. Instead, there are only a bunch of guidelines, definitions and dos and don’ts. There are no practical suggestions, implementation standards, templates or even a methodology. It’s a concept that somehow became popular leaving the implementation details to you.

Curiously, so many data mesh concepts have already been done in some way or another in the Data Vault 2.0 world.

In fact, we know of one large company that decided as an organization to embrace mesh concepts. They realized they could lean on the Data Vault 2.0 system to implement the data mesh. Since then, using the Data Vault 2.0 solution with data mesh has become far more common, and companies are seeing and experiencing success with this strategy.

The 5 W’s (Who, What, When, Where and Why) related to the Data Mesh is a theme this year that is not to be missed! You’ll experience both concept analogies with Data Vault 2.0 as well as the experience of actual implementers both from the stage and in the audience – truly a unique experience!

Generative AI and Its Potential (ML – Dynamic Data Warehousing, Taxonomy / Ontology discovery, Dynamic Linking, AI driven business metrics, and more)

In the last year, the biggest industry disruptor has been generative AI. Considering its different approach to training a machine and its accessible natural language interface, it’s no wonder that tool vendors are scampering to incorporate it into their platforms.

But Generative AI has applications far beyond just doing your kid’s homework.

In fact, Generative AI is now being tied into everything from data modeling tools all the way to data integration as a method of providing suggestions. However, even generative AI is dependent on source data for learning, as well as the right prompts to answer questions with relevance. While of course there are certain aspects that can accelerate a build, providing an AI tool with poor data could increase your problems exponentially.

The problem with the current marketing and hype around AI is that it continues to push this technology as an end-to-end solution, when in reality it is assistive tooling at best. At worst, ignore the basic best practices and you could end up with more problems than solutions.

Technology can optimize work via automation and generation, but it cannot replace humans. It is imperative to leverage any AI in the right way, to provide increased output without neglecting the necessity of a human factor to appropriately direct and configure your tools. This is where our sessions come in!

Some sessions within this theme will be exploratory, with thought leaders speaking on how to leverage Generative AI for concepts such as Dynamic Data Warehousing. But there are practical applications such as discoveries of Taxonomies and Ontologies that it’s already being used for that we’ll discuss too.

There’re also potential exploratory applications such as dynamic linking and AI-driven business metrics extracted from datasets automatically. If it works on a solid foundation such as a Data Vault 2.0 Enterprise Data Memory archive, the potential is multiplied manifold.

Again, even something as flashy and disruptive as Generative AI is dependent on the quality, quantity, and completeness of the input data. With this in mind, we will consider Data Vault 2.0 as an excellent and proven methodology, the only complete solution for analytics and information management across people, process, and technology. While the Data Vault pioneered automation in the analytics space, Generative AI has the potential to take this to the next level to accelerate deliveries of your artifacts within the DV 2.0 solution. DV 2.0 is naturally one of the best ways to leverage these new tools, technologies and ideas while continuing to build long-term optimal solutions.

Combining Generative AI and Data Vault 2.0 principles would be like legally putting it on steroids! However, this comes with risks which we need to be cognizant of. We will consider all of this and more in sessions at WWDVC 2024!

Business Track: Executive’s Guide to Data Quality and Digital Transformation Leadership (Catalogs, business glossaries, Taxonomies, Ontologies, and AI / ML for enriching / enhancing / enabling faster automation)

Last year was our first with a dedicated business track; it was so well-received that we’ve decided to do it again.

It’s a known reality that generally, your business executive doesn’t really care what you use, provided it works and doesn’t often need re-engineering.

It’s no wonder that the Data Vault 2.0 solution is becoming their favorite, owing to its well thought out design across people, process, and technology.
This track, presented by business executives themselves, will help you understand how the business side of your organization thinks, so that before you meet to get funding for your projects, you know just what they’re looking for and how to present it in the correct language.

While it’s called the executive track, I’d strongly encourage all practitioners to attend this part of the event. Why? 2 Reasons:

• Because the Data Vault 2.0 Solution was, is, and always will be about the business. Therefore, understanding of data catalogs, business glossaries, taxonomies, ontologies and what the business is looking at in terms of new technologies and concepts is paramount.
• While machines provide a certain level of mechanized and artificial intelligence, analytics teams should provide business intelligence and insights to make yourself truly invaluable to the organization. Want to know why an executive invests in certain tools, technologies, methodologies, and solutions in this disruptive period? Don’t miss this.

As you can see, it isn’t even 2024, and yet this conference is already taking shape! As always there’s something for everyone here and therefore if you’re in the analytics space, you don’t want to miss this chance to hear the best industry thought leaders’ take on these subjects. Better yet, have you considered applying to speak on one or more of these topics? Be on the lookout for our call for speakers! We look forward to seeing you at WWDVC 2024!