Wednesday, March 26, 2014 |
News Highlights
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Tony Rathburn
The vast majority of predictive
analytics projects can be conceptualized as falling into one of four
basic types, from which we can creatively combine the benefits of
each to enhance our organizational performance.
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Poulomi Damany
Analytics tools and platforms must
evolve to enable the promise of big data, including mining the most
from semi-structured data.
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Tom Hammergren
In the last part of our series, we
examine the business-driven context for BI and the link between the
agile development and a business's agility imperative.
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Stephen Swoyer
With Yellowfin 7, Yellowfin business
intelligence gets a branding makeover -- from a simple BI platform
to an "analytics platform." It's a departure from Yellowfin's
traditional messaging, but according to CEO Glen Rabie, the company
has been an analytics powerhouse all along.
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TDWI Webinar Series:
Speaker:
Philip Russom
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There's a fair amount of confusion about
how best to collect, integrate, and preprocess data for advanced
analytics. Many BI and data warehouse professionals think it's the
same as the traditional ETL practices they've applied to their
report-oriented data warehouses for years. Some database
administrators think it's just a matter of dumping large volumes of
data into a highly scalable repository. |
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Upcoming Webinars of Interest
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It's important to know your data, yet
many organizations lack fundamental knowledge about their data. The
situation is getting tougher as "big data" sources grow and
documentation efforts can't keep pace. Good data knowledge is
critical to defining business objects; poor understanding leads to
higher costs, embarrassing mistakes, regulatory errors, and data
quality problems that damage daily decision making.
Speaker:
Dave Stodder
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Register
Now
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Find out how your organization can
achieve new advantages through the visualization and analysis of
real-time data and event streams.
Speaker:
Dave Stodder
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Register
Now
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Events Calendar
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