Thursday, July 13, 2017

Test (and raise) your IQ on data lakes; AI must be bias-free to flourish; Python in SQL Server

Information Management Digest

A roundup of information management content from TechTarget's network | July 13, 2017

TechTarget
FEATURED STORY
Quiz: What's your IQ
on implementing and managing data lakes?
By Tréa Lavery, Editorial Assistant

A data lake is a form of big data architecture that can provide lots of analytics value to an organization. This quiz can tell you if you know what it takes to deploy and manage one; it also contains info about data lakes to help boost your knowledge.
(SearchDataManagement.com)

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NEWS
 
Building AI apps free from bias crucial to avoid analytics errors

Biased data samples or analytical model development practices can derail companies interested in using AI tools and diminish the technology's return on investment.
(SearchBusinessAnalytics.com)

 
MongoDB 'Charts' a way to data visualization from its database

MongoDB is targeting better data visualization with MongoDB Charts, an upcoming tool that adds another means for business users trying to look into their pools of NoSQL data.
(SearchDataManagement.com)

 
Azure SQL Data Warehouse expands processing power

Spirited competition is under way among cloud providers as they enhance large-scale relational data warehouses in the cloud. An Azure SQL Data Warehouse update is the latest example.
(SearchSQLServer.com)

 
Creative AI takes machines into uncharted analytics territory

Artificial intelligence and creativity may not seem like the most natural pairing, but some AI developers are trying to show that machines can replicate much of human creativity.
(SearchBusinessAnalytics.com)

EXPERT ADVICE
 

What you need to know to run SQL Server Python applications

From installation to implementation, here are the basic details on how to take advantage of the Python programming language for analytics applications in SQL Server 2017.
(SearchSQLServer.com)

 
Data managers apply data governance process on the sly

Data clearly needs to be governed, but data management teams increasingly are approaching governance in subtle ways to avoid being seen by business users as the data police.
(SearchDataManagement.com)

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