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Big Data & Analytics

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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.
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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.
Derek Rodriguez
A data lake can be tremendously beneficial to organizations looking to acquire enterprise-wide content from multiple sources and extract insights from it. In a recent project for a pharmaceutical client, we leveraged Aspire for Big Data to ingest over one petabyte of unstructured content into their data lake. Read the firsthand story from our architect.
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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.