Thursday, June 28, 2018

How Hadoop data lakes challenge tech teams; MongoDB gives users ACID; tips from Gartner on finding data scientists

AI, Analytics and Big Data Digest

Artificial intelligence, BI and data management content from TechTarget | June 28, 2018

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Hadoop data lakes test IT teams on data integration, curation
By Jack Vaughan, Senior News Writer

IT managers from Hilton, United Airlines and Verizon Wireless talk about building Hadoop data lakes to support new analytics and operational applications -- and the challenges their teams face on integrating, ingesting and refining data for end users.
(SearchDataManagement.com)

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NEWS
 
MongoDB 4.0, Stitch aim to broaden use of NoSQL database

NoSQL vendor MongoDB upgraded its database software with ACID transactions support, while also releasing a serverless platform that's intended to simplify application development.
(SearchDataManagement.com)

 
Three factors for protecting sensitive data in the GDPR era

Data privacy is a hot topic nowadays thanks to the EU's General Data Protection Regulation and Facebook. But how do data security, access control and data protection differ?
(SearchDataManagement.com)

 

Generative adversarial networks could help improve AI algorithms

Generative adversarial networks, or GANs, that pit different algorithms against one another could make AI applications more creative -- and improve the accuracy of the algorithms.
(SearchEnterpriseAI.com)

 
Computer vision technology helps Trulia link buyers to homes

In this podcast, Trulia VP of engineering Deep Varma discusses the importance of computer vision applications to the real estate website's overall goal of helping buyers find homes.
(SearchEnterpriseAI.com)

EXPERT ADVICE
 

Building a data science team in today's data-centric climate

Finding and training data scientists to build a data science team can be challenging. In a recent webinar, Gartner analyst Peter Krensky offered tips on how to do it successfully.
(SearchBusinessAnalytics.com)

 
What goes into a customer data analytics integration framework

Customer data integration is a minefield for IT teams to navigate. But incorporating a set of core technical functions into an integration architecture can ease the process.
(SearchDataManagement.com )

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