Openness was a common refrain at Insight 2015, and the opportunities of open systems, technologies and the IBM analytics platform are abundant. Check out some observations from the conference and a few shining examples from its demo center.
Three capabilities can take a streaming analytics solution to the next level: time to value, application intelligence and insight confidence. All of these must be taken into account when turning an adequate analytics system into a great one.
Find out how Day 3 of the conference offered insight into how data scientists have benefited from the latest approaches to web-scale analytics, including open sourcing of the System ML machine learning library to help the Spark community.
From the time we were little, sharing has been an important concept. And even though sharing can be a double-edged sword in the business world, open source initiatives serve to prove its value. When considering open and unified analytics platforms, make sure they embrace three elements: inclusion,
As one principle of the buffalo theory demonstrates, open source projects are applying a process of natural selection through the manner in which they tackle performance bottlenecks and other obstacles that can prevent further technological advancement. By continually identifying and addressing the
At the Spark Technology Center, headquartered in San Francisco, you can build algorithms that drive deep intelligence into every application and share experiences to achieve success, fast. And more than a physical location, the center is a community that works together to showcase the true
Time series data can contain highly valuable insights—if organizations can detect and classify the events within it. An approach that combines stream processing and machine learning holds the key to analyzing large, fast data streams.
Apache Hadoop has been around for a decade, but what is it exactly? Get a quick primer on Hadoop’s four key modules and how they enable this open source framework to handle storage for massive volumes of big data that can used for advanced analytics.
What a shame. Most businesses aren’t taking advantage of their data, leaving them hungry for success. According to Forrester Research analyst, Michele Goetz, only 12 percent of available data is used. If I am any good at math, that means there is a lot of data that is not being used.
In the world of big data, the elephant is king. Hadoop, whose elephant logo has become the face of big data, has been joined in the big data jungle by many friends: Pig, Jaql and even a ZooKeeper to keep them all in line. The entire big data jungle will be making a trip to Las Vegas in October for
IBM has a long and successful history with open source, from running Linux on IBM PCs to contributing initial codebase for Eclipse. We believe a mix of open source and closed source is the best way to drive adoption in the marketplace. Having the full support of a vendor like IBM can lower risk
As part of IBM's ongoing commitment to Hadoop and the broader open source ecosystem, IBM is joining forces with Databricks, Cloudera, Intel and MapR to broaden support for Apache Spark. IBM's goal is to provide enterprise customers with access to the latest innovations around big data and analytics.