Thursday, August 23, 2018

5 top data science tools: Python, R and more; AI personalizes e-commerce sites; the case for open source RDBMS software

AI, Analytics and Big Data Digest

Artificial intelligence, BI and data management content from TechTarget | August 23, 2018

TechTarget
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Data scientists weigh in: 5 data science tools for users to consider
By Ericka Chickowski, Contributor

The surge of data captured by organizations today often requires the use of data science tools to fully analyze and understand the information. We asked data scientists what tools they're using -- here are the top ones they pointed to.
(SearchBusinessAnalytics.com)

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NEWS
 
AI makes e-commerce sites more responsive to customers

AI tools are giving a boost to personalization efforts in e-commerce as companies find that machine learning tools can make ads and user experiences more relevant to their customers.
(SearchEnterpriseAI.com)

 
Chief data officer skills tested by AI technology blitz

Sessions at a recent MIT symposium provided insights on chief data officer needs, as the AI wave starts to hit IT teams and affects CDOs more than most other tech trends.
(SearchDataManagement.com)

 

Lower costs, cloud options spur open source RDBMS uses

Open source technologies have become more capable alternatives to mainstream relational databases for cost-conscious users -- and the cloud is making them more accessible.
(SearchDataManagement.com)

 
Data science in healthcare demands dual focus, user says

Symphony Post Acute Network is blending analytics for clinical and business operations, a change in how healthcare systems have traditionally approached analytics.
(SearchEnterpriseAI.com)

EXPERT ADVICE
 

2 ways to attach SQL Server files to Linux containers

SQL Server database files can be stored outside of Docker containers in host directories or volumes. Here's how to set up SQL Server on Linux databases and attach them to containers.
(SearchSQLServer.com)

 
Offset IoT network demand with an edge analytics strategy

As more organizations add IoT devices, incoming data streams risk overloading their IoT environments. But an IoT edge analytics system could help distribute the workload.
(IoTAgenda.com)

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