Thursday, October 26, 2017

Tableau lessons learned lead to better BI dashboards; Microsoft, Oracle up their cloud database games

Information Management Digest

A roundup of information management content from TechTarget's network | Oct. 26, 2017

TechTarget
FEATURED STORY
Better implementation of Tableau systems gives BI dashboards a boost
By Ed Burns, Senior News Writer

Building Tableau dashboards is about more than just creating pretty data visualizations. The process should also incorporate strong data management practices and a sharp business strategy, say users who have made changes to improve their Tableau implementations.
(SearchBusinessAnalytics.com)

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NEWS
 
Cloud databases get stronger push from Microsoft, Oracle

Using cloud databases is now more a matter of when than if at many companies. There's also the question of how, as Microsoft, Oracle and AWS square off against one another.
(SearchDataManagement.com)

 
Big data systems lead users
down new business paths

Organizations hungry for more revenue are using Hadoop and other big data technologies to break their existing business molds and pursue new strategies and product offerings.
(SearchDataManagement.com)

 
Visual data exploration a key first step for deeper analyses

Visual data analysis is an important first step in any advanced analytics project -- and data scientists and other analysts who overlook it do so at their own peril, experienced users warn.
(SearchBusinessAnalytics.com)

 
NewSQL databases rise anew -- MemSQL, Spanner and others

The NewSQL database was almost hidden when Hadoop and NoSQL arose. Now, as more big data teams move toward production uses, NewSQL products may get a second look.
(SearchDataManagement.com)

EXPERT ADVICE
 

Machine learning not magical in Oracle's autonomous database

Oracle is touting a new autonomous database as part of its drive to the cloud. The Oracle 18c software relies on machine learning, but the effect is more evolutionary than revolutionary.
(SearchOracle.com)

 
Data quality for big data should include a focus on usability

To make big data analytics applications more effective, IT teams should augment conventional data quality processes with measures aimed at improving the usability of data.
(SearchDataManagement.com)

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