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Big Data & Analytics

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
As businesses increasingly rely on big data to discover better insights, the right techniques and methodologies, known as responsible data science, are key to helping overcome biases and ensure responsibility. Applying a gardening analogy to data science, we'll discuss five essential elements that businesses should consider before jumpstarting a data, specifically search/analytics, project.
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
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.
Paul Nelson
Today's businesses hold large volumes of valuable data that provides immense insights to support business decisions, customer services, and operational efficiency. It can be daunting to manage this amount of data. And with the EU's GDPR being rolled out soon, businesses may face even more challenges to stay compliant. Here are 10 things you may be missing but probably should consider doing, and why.
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.