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Big Data & Analytics

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The Adobe Experience Manager (AEM) connector is the newest addition to our growing range of connectors designed to support secure data connectivity between search engines and third-party repositories. Read more about the AEM connector's features and use cases.
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Enterprises are increasingly seeking innovative systems to better leverage unstructured, natural language content to deliver actionable business insights. We are pleased to introduce Saga – a scalable, easy-to-use natural language understanding framework that enables non-data scientists to create and maintain powerful and flexible enterprise language models for user interaction and document understanding.
Kamran Khan
Organizations are increasingly becoming insight-driven. Together with the rapid development of AI technologies like machine learning and NLP, the demand for AI-enabled search and analytics solutions will become more prevalent. As we begin 2019, our Managing Director, Kamran Khan, shares some of the most notable observations around these capabilities.
Paul Nelson
In his years as a search engine programmer and architect, our Innovation Lead, Paul Nelson, has come across lots of business-critical as well as creative uses for search engines. Here’s a roundup of 10 prevalent search enterprise use cases he has helped organizations explore and implement over the years.
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In this blog post, we discuss how Artificial Intelligence (AI) and Natural Language Processing (NLP) techniques can be used to create knowledge graphs, which can then power chatbots, question/answer systems, and search engines to deliver holistic enterprise knowledge and improve business outcomes.
Jonathan Blasenak
Solr vs. Elasticsearch has been discussed so frequently on our blog and within the enterprise search community. But as traditional enterprise search has evolved into what Gartner calls “Insight Engines,” we revisited this topic to provide the latest observations, including cloud deployments, integration with big data analytics, and cognitive search capabilities. Read on to find out the key criteria to consider if you’re weighing between Solr and Elasticsearch in 2018.
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Developed by our team at Accenture Applied Intelligence and our partner Microsoft, this demo leverages Aspire Content Processing and Azure Cognitive Services to enhance unstructured data preparation, enabling advanced, cognitive search functionalities in Azure.
Asha Narasimha
New innovations have been rapidly accelerated by big data analytics, artificial intelligence, cognitive computing, and machine learning. Interestingly, a common theme emerged: search is the stepping stone and enabler of these technologies. Read this blog to see how search opens new doors for insight discovery across all enterprise functions.
Laurent Fanichet
How is cognitive search empowering users beyond the traditional search boxes and keyword matching? Read this post from our guest blogger, Laurent Fanichet at Sinequa, to see how big data, natural language processing, and machine learning are making search smarter for modern organizations.
Carlos Maroto
A critical part of a data lake implementation is having effective mechanisms for the data to be copied from different repositories to the data lake. In this blog, our architect discusses potential challenges, best practices, and common methods for data acquisition as well as how to select the most appropriate implementation approaches for your data lake use cases.