News
News
- April 12, 2017
12 Apr'17
Sisense jumps on the smart data discovery trend with new update
Sisense is betting that machine learning algorithms can improve its data discovery experience, a move that could soon become the new standard in self-service analytics.
- April 06, 2017
06 Apr'17
Tableau pricing shifts to subscription to keep up with market demands
The cost of Tableau software for most new customers will be calculated based on subscription fees rather than licenses, in a reaction to emerging market demands and challenges.
- March 28, 2017
28 Mar'17
Self-service BI and analytics tools face evolving set of challenges
Self-service BI tools have become the go-to standard for business intelligence software, but users are pushing vendors to rethink how they address enterprise needs and advanced analytics.
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- March 17, 2017
17 Mar'17
Ease of use is top priority in selecting self-service analytics tools
A lot of factors go into a choosing a strong, modern BI tool. But several users say ease of use trumped all other considerations for them in picking self-service software.
- March 08, 2017
08 Mar'17
Analytics teams give data science applications real scientific rigor
Data scientists at companies such as LinkedIn and Cisco are applying aspects of the scientific method to data mining and analysis initiatives to try to make sure they get valid results.
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Sponsored News
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- February 28, 2017
28 Feb'17
Successful data science process not simple to set up, sustain
Data science teams face a mix of process and cultural challenges in organizations, according to experienced analytics managers who offer advice on how to overcome the hurdles.
- February 15, 2017
15 Feb'17
Spark gives genomic data analysis applications a big data charge
Scientific researchers need robust big data architectures to solve the challenges of mining and analyzing genomic data, and some say the Apache Spark engine is well-suited for the job.
- February 13, 2017
13 Feb'17
Enterprise Spark maturity is still a work in progress
There's no doubt the maturity of Spark development for enterprises has come a long way, but it may still be too 'techy' for some businesses.
- February 06, 2017
06 Feb'17
Data-driven business models lead the way forward
Good instincts used to drive successful business strategies, but intuition just can't cut it in the age of big data.
- February 06, 2017
06 Feb'17
Tools for predictive analytics took a hit in presidential election
Tools for predictive analytics can help guide decision-making in companies and political campaigns, but the 2016 election showed that emotion is still a powerful factor for voters.
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- February 06, 2017
06 Feb'17
Don't learn lessons on predictive modeling techniques the hard way
Deploying and using predictive modeling tools without heeding best practices doesn't guarantee analytics success, a fact that many analytics managers and election forecasters know all too well.
- January 11, 2017
11 Jan'17
Lack of skills remains one of the biggest data science challenges
Many enterprises are struggling with the complexity of today's big data and data science ecosystem, though they recognize the opportunity of emerging practices.
- December 23, 2016
23 Dec'16
Not all machine learning and AI projects panned out in 2016
Artificial intelligence applications were all the rage in 2016, but while some delivered impressive results, others didn't work quite as well as developers planned.
- December 22, 2016
22 Dec'16
Events of 2016 put strain on predictive analytics algorithms
The world started to seem like a less predictable place in 2016, and that should throw up caution flags to businesses that heavily leverage predictive analytics models.
- December 21, 2016
21 Dec'16
Why 2017 is setting up to be the year of GPU chips in deep learning
GPU technology, once primarily the domain of computer gamers, is getting new legs in systems that run deep learning and AI applications. Experts predict it will be a big part of analytics in 2017.