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Ten Tangible Ways Data Virtualization Fuels AI/ML

Blog: The Tibco Blog

I was recently asked to speak about Artificial Intelligence and Machine Learning  (AI/ML) in the AI and Machine Learning Theatre during the October 2018 Big Data World Singapore event.  

I was excited about the opportunity as well as the intellectual challenge of speaking about this dynamic subject area.  While I have written a lot about AI/ML, for example in Why Artificial Intelligence Dominates 2018 Technology Predictions and Five Steps to Jumpstart Your AI Success, I don’t consider myself an AI/ML expert. However, as co-author of the first book on Data Virtualization, I am considered by many to be somewhat of an authority on data integration. So in my talk,  Best Practices for Delivering the Data That Fuels AI/ML, I decided to bridge these key subject matters by showing how data virtualization can help accelerate AI/ML success.

Bridging AI/ML and Data Virtualization

I thought it was important to make this bridge. Why?  It is pretty simple. From a business value point of view, organizations value AI/ML because they understand how it can enable innovative new products, compelling customer experiences, and optimized operations and digitally transform businesses. To make it work successfully, however, requires data. Your AI/ML algorithms are only as good as the data that fuels them.  And in today’s complex data landscape, data can be a big bottleneck.

I thought the audience would enjoy learning about how data virtualization could help address this AI/ML data bottleneck.  And it turns out, based on the standing room only crowd and the hour I spent afterward answering questions, that I was right.

Ten Tangible Ways Data Virtualization Fuels AI/ML

While I cannot share the content of this entire presentation in this short blog, l can give you the highlights. In particular, let me share the following ten tangible ways that TIBCO® Data Virtualization can help you overcome you’re AI/ML challenges and fuel your AI/ML-driven digital transformation.

  1. Business Directory makes AI/ML data easier to find
  2. Data Abstraction makes AI/ML data easier to understand
  3. Standard Data Delivery Interfaces support heterogeneous AI/ML solutions
  4. 100+ adapters broaden AI/ML data access
  5. Data Federation provides the complete picture
  6. Query Optimization ensures timely data delivery
  7. Quality Ensures high-integrity, trusted data
  8. Integrated security controls AI/ML data access
  9. Studio Accelerates AI/ML dataset development and time-to-solution
  10. Scalability supports multiple lines of business, hundreds of AI/ML applications, and thousands of AI/ML users

If you are developing new AI/ML solutions and are challenged getting the data you need to fuel them, you can learn more about TIBCO’s Data Virtualization offerings here.

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