Summary
Here, and in the previous few chapters, we have helped to provide you with a broad overview and real solutions to apply the capabilities by combining Azure Cognitive Services technologies. Many organizations struggle with leveraging the significant volumes of data that lie in storage and file shares untapped for the significant value they hold. Beyond simply returning search results and bringing the data to the surface, we can also begin to analyze the data deeper and begin mining the data for other potential uses of AI by building machine learning models to predict future results.
A fully built KM solution is no small undertaking, but the value can greatly outweigh the costs of deployment and services. A small proof of concept to surface some of the details of latent data could be a great place to start, and relatively cost-effective. After making a case for a full implementation, you can harness all the power of the full solution we laid out in these chapters. Whether...