“Key industries including healthcare, retail, telecommunication, media and entertainment, financial services and the government leverage NetApp solutions to manage large amounts of content, expand technology infrastructures without disrupting operations, and improve data-intensive workflows.”
In this video from the GPU Technology Conference 2014, Ami Gal from Sqream Technologies describes the company’s innovative Big Data processing technology. “Can you compare the technology of today with the technology of tomorrow? Yes, with SQream Technologies you can. This is because SQream Technologies uses GPUs to capture, store and process Big Data within seconds, resulting in 100x faster insights. Big Data analytics, once considered unattainable, can now be achieved in a matter of seconds with SQream’s hassle-free, robust analytic database.”
I’ve been monitoring an interesting discussion on the Big Data and Analytics group over on LinkedIn – “Is there a difference between big data and small data?” It is an interesting question, one that I’ve heard before during my travels down in the trenches as I explore our industry.
Last night I attended the Los Angeles Hadoop users Group (LA-HUG) meeting hosted by Shopzilla. The topic for the evening was “An Overview of Hulu’s Data Platform” presented by Prasan Samtani and Tristan Reid of Hulu. From all indications, Hulu is a significant player in the Hadoop user community and this talk documented the team’s command of big data technology.
“Machine logs contain simple and complex data – some logs contain time stamped data (i.e. syslogs) that are tactical events or errors used by sys admins to troubleshoot IT infrastructure. But other logs have more complex, unstructured or multi-structured text with sections on configuration info, statistics and other non-time stamped data. To make sense of the data in these logs, one needs a powerful language and processing engine to provide meaning and structure to the information. Once structure is defined, complex analytics and trend reporting can be performed.”
“Intel’s goal is to encourage more innovative and creative uses for data as well as to demonstrate how big data and analytics technologies are impacting many facets of our daily lives, including sports. For example, coaches and their staffs are using real-time statistics to adjust games on-the-fly and throughout the season. From intelligent cameras to wearable sensors, a massive amount of data is being produced that, if analyzed in real-time, can provide a significant competitive advantage. Intel is among those making big data technologies more affordable, available, and easier to use for everything from helping develop new scientific discoveries and business models to even gaining the upper hand on good-natured predictions of sporting events.”
“Active archives are ideal for organizations that face exponential data growth or regularly manage high-volume unstructured data or digital assets. Target markets include life sciences, media and entertainment, education, research, government, financial services, oil and gas, and telecommunications, as well as general IT organizations requiring online data archive options.”
Big Data will change the way your organization responds to business opportunities. But to reap its full benefits, you have to move from proof of concept into full production. Here is an informative, 52-minute presentation that provides the guidelines for successfully integrating Hadoop into your standard data center processes.