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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.
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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.
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Developed by our team at Accenture Applied Intelligence and our partner Microsoft, this reference architecture 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.
Carlos Maroto
Data lakes bring together data from disparate sources, making it easily searchable in order to support your organization's information discovery, analytics, and reporting. But how do you put in place appropriate security measures to ensure your data is well-managed and protected? In this blog, our expert will discuss four key areas you should consider when implementing data lake security.
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In March 2018, we are pleased to announce the Aspire 3.2 Big Data Release, which delivers some innovative advancements that are worth noting. Key highlights include the successful integration with the Hadoop ecosystem as a Cloudera parcel and the use of HBase and MongoDB. The new functionalities bring unlimited scalability, making Aspire more compatible with the big data ecosystem.
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In September 2017, Oath, a Verizon company, announced that it would open source Vespa - a powerful but largely unknown big data processing and service engine. So what value does Vespa add to the big data analytics space? Here are some of our initial observations.
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Big data analytics, machine learning, and AI have evolved rapidly, allowing enterprises to better use data to produce transformative results. We've seen the expansion of these technologies in our clients’ projects that combine search with NLP, machine learning, and big data to build AI-assisted systems. This blog summarizes some key points on “the rise of AI” and how it can impact your business.
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As we transition to Accenture, on November 1, 2017, we will be retiring Search Technologies’ social media channels and moving our conversations to Accenture Analytics. Follow us on our Accenture Analytics channels to continue getting the same search and big data analytics insight, news, blogs, and resources to which you've been accustomed.