- June 29, 2017
A new breed of data analytics tool for data scientists aims to deliver far more than BI software, including predictive analytics and exploratory analytics.
- June 22, 2017
Running business intelligence applications in the cloud has yet to take the BI world by storm. Researcher Howard Dresner offers insight on why and discusses the state of cloud BI software.
- June 07, 2017
When deploying deep learning models into production, experts say it's important to take care of the basics, like model design and testing, to ensure optimal business impact.
- June 06, 2017
Databricks brings new features to its managed Spark platform -- as well as to open source Spark -- that it hopes will make the computing engine more widely usable.
- May 23, 2017
Hiring a data scientist is hard enough given the shortage of candidates, but the subtle mix of skills required by the job can make hiring one even harder.
Sponsored by CloudHealth - As enterprises continue to add new use cases and workloads to their cloud portfolio, the stakes keep rising for potential governance speed bumps. Business users and IT professionals alike are now using the cloud for everything from compliance and security to cloud-native application development and infrastructure optimization. But this makes policy management more difficult, time consuming and costly, especially with so many cloud services being purchased and deployed outside the scope, visibility and control of a centralized IT operations group. See More
Sponsored by CloudHealth - In the era of Cloud 1.0, early adopters were often drawn to the cloud because it allowed them to reduce Capex and move to a more predictable subscription pricing model. In recent years, cloud adoption has surged because organizations have recognized that it not only reduces their hardware purchases and per-seat software licenses but provides many operational benefits as well. See More
Sponsored by CloudHealth - For more than a decade, the biggest gating factor in cloud computing adoption was perceived security risks. IT professionals and business leaders alike were often extremely concerned about a perceived loss of control of mission-critical data and essential applications when moved to the cloud. See More
- April 19, 2017
To get the most value from investments in advanced analytics techniques, like artificial intelligence and data science, businesses must embrace a specific mindset.
- April 12, 2017
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
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
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.
- March 17, 2017
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
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.
- February 28, 2017
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
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
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
Good instincts used to drive successful business strategies, but intuition just can't cut it in the age of big data.