Evaluate

Big data analytics

• IBM's Watson Analytics makes strides but gives off bad vibes

  Watson Analytics is a strong player in a formidable field that includes Google and Adobe. It does perform as advertised -- but IBM's AI-driven analytics technology leaves a lot to be desired. Continue Reading

• Real-time streaming analytics systems need help from message brokers

  Real-time analytics applications typically involve multiple streams of data that need to be properly organized and coordinated, a job that calls for new message queuing technologies. Continue Reading

• Streaming data analytics puts real-time pressure on project teams

  A real-time data architecture that can support streaming analytics applications is an enticing, yet daunting, prospect for organizations looking to act quickly on information. Continue Reading

• 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. Continue Reading

• Prescriptive models take analytics one step beyond

  Descriptive analytics is powerful. Predictive analytics, flashy. Prescriptive analytics? Boring, perhaps, but no less essential to improving operations in the enterprise. Continue Reading

• Predictive analytics tools hinge on good data, business expertise

  Predictive analytics helps businesses maintain a competitive edge, but only with the right data. And even then, the most advanced analytics tools can't replace expertise.Continue Reading

• Analytics VP shares best practices for hiring data scientists

  Data scientist jobs can be notoriously difficult to fill, but businesses can turn to tools that fill in gaps in staffing and take care of their analytics needs.Continue Reading

• Debate over big data and privacy is just getting started

  For years, the tension between privacy and big data has been apparent, but with emerging technologies generating huge amounts of data, the debate will intensify.Continue Reading

• Advanced analytics techniques, tools came to the fore in 2016

  This year saw huge hype around advanced analytics tools like AI and machine learning. This podcast recaps everything businesses need to know about this year's top analytics trends.Continue Reading

• Siemens uses process mining software to improve manufacturing visibility

  Prior to implementing process mining tools, manufacturer Siemens had little visibility into production bottlenecks and other operational issues. Now, it can see the sources of the problems more clearly.Continue Reading

• Machine learning models take over the software industry

  Just as software took over the broader technology industry a few years ago, we're starting to see machine learning algorithms dominate software. There's good reason for this trend.Continue Reading

• Machine learning projects face data prep, model building hurdles

  IT and analytics managers discuss the biggest challenges of machine learning applications, with data preparation and development of algorithm-driven analytical models sharing top billing.Continue Reading

• Artificial intelligence tools may be for real this time

  We've seen AI technology get hyped in the past much like we're seeing today. But there may be reasons to believe that AI is for real this time around.Continue Reading

• Emerging analytics tools challenge dominant big data philosophy

  Analytics technologies like the internet of things and cognitive computing mean we cannot have all the data on a given subject. So, what does that mean for big data?Continue Reading

• IT managers weigh in on biggest benefits of big data analytics

  Experienced big data project managers and professionals detail the top business benefits that their organizations are getting from deployments of Hadoop and Spark analytics systems.Continue Reading