Archive for category Wikibon
The biggest week of the Big Data calendar is here. Kicking off tomorrow #theCUBE is live at #BigDataNYC 2014 for two days of continuous coverage. We’ll be interviewing Big Data practitioners, thought-leaders and technologies live from the Hilton Times Square in New York City. Watch live coverage at live.siliconangle.tv.
On Thursday (10/16) afternoon, tune in to catch my presentation to capital markets professionals on the state of Big Data in the enterprise, the implications for IT heavyweights (Oracle, SAP, Teradata, etc.) and what savvy investors need to consider when placing their bets on the Big Data market. Following my presentation, we’ll have a live panel discussion to continue the conversation. Panelists include myself former Nokia Big Data team lead (and current Cloudera Big Data Evangelist) Amy O’Connor, Big Data Guru and CEO of Tresata Abhi Mehta, and former Cowen and Company software analyst Peter Goldmacher.
Ed Walsh, the CEO whiz kid is back doing what he does best – running a product company. This time he’s landed at Catalogic Software, a firm many people have never heard of—but probably will over the next several months.
Walsh is a storage industry veteran who is best known for taking small, relatively unknown product-focused companies that need clearer strategy and execution chops, building a team, pointing them at a problem, gaining traction and then selling to a larger player who needs to fill a gap. Walsh touts an impressive list of successful exits as a CEO, including Avamar (EMC), Virtual Iron (Oracle) and Storwize (IBM).
The “big four” megatrends of cloud, mobile, social and Big Data are putting new pressures on IT departments. These high level forces are rippling through to create demands on infrastructure as follows:
Cloud – Amazon has turned the data center into an API. This trend is forcing CIOs, as best they can, to replicate the agility, cost structure and flexibility of external cloud service providers. Unlike outsourcing of the 1990’s, which had diseconomies of scale at volume, cloud services have marginal economics that track software (i.e. incremental costs go toward zero). This trend will put added pressure on IT to respond to the cloud.
Despite the apparent contradiction, Hadoop and other emerging Big Data approaches are at the same time complementary to and disruptive to established data warehousing and business intelligence practices in the enterprise. I recently spoke with my colleague Stu Miniman about this and other findings from Wikibon’s Q2 2014 Big Data Analytics Survey in the below Cube Conversation. The survey, one of two major Big Data surveys Wikibon will undertake this year, is part of Wikibon’s new Big Data research service. The new service is focused on primary data-driven research designed to uncover how Big Data is practically applied in today’s enterprise, explore the impact on existing modes of data management and analytics, and to understand its implications for existing and start-up Big Data vendors. To find out more about Wikibon’s new Big Data research service, please email
Tape is Dead, Not!
The combination of tape and flash will yield much better performance and substantially lower cost than spinning disk. This statement will prove true for long-term data retention use cases storing large data objects. The implications of this forecast are: 1) Tape is relevant in this age of Big Data; 2) Certain tape markets may actually show growth again; 3) Spinning disk is getting squeezed from the top by flash and from below by a disk/tape mashup we call “flape.”
Spinning Disk: Slow and Getting Slower
This week there are two important enterprise technology conferences taking place. One – SAPPHIRE 2014 – will see an old guard enterprise tech giant attempt to show it is capable of adapting to a technology landscape increasingly dominated by the cloud and Big Data. The other – Hadoop Summit 2014 – will see dozens of start-ups born in this new world out to prove to cautious CIOs that their technologies and platforms are ready for enterprise-level workloads.
It’s an interesting juxtaposition. SAP is determined to join the ranks of the “cool” cloud and Big Data companies (Salesforce.com, Hortonworks, Amazon Web Services), while those cool companies are equally determined to join the “enterprise-grade” club dominated by IBM, Oracle and, yes, SAP.
It isn’t the zombie apocalypse, but for too long, IT administrators have been shackled to infrastructure that was as friendly and stable as the stumbling undead. The coordination between application, infrastructure and physical data center was poor, leading to over 70% of resources being spent on adjusting configurations and trying to keep the lights on. Hyperscale cloud providers were built for scalability from day 1, so they had to be able to manage orders of magnitude more gear with a smaller IT staff. While cloud providers can customize new applications, enterprise users are burdened with a portfolio of legacy applications. The transformation to a scalable, agile and fast methodology isn’t simple, there are lessons and technologies that the enterprise can learn from the largest IT shops.
Amazon has turned the data center into an API and that has created a dramatic shift in the enterprise. The Internet giants – we sometimes refer to them as the hyperscale crowd (e.g. Amazon, Google, Microsoft, Apple, Facebook, etc.) – are paving the way for the next generation data center. This brings several challenges to IT organizations including pressure from the corner office to replicate the speed, agility and efficiency of these innovators. The problem is, most IT organizations don’t have the engineering capacity of a Google. IT organizations will spend money (with a vendor) to save on management costs (i.e. they’ll buy a more expensive solution that is easier to manage). Internet giants on the other hand will spend time (engineering time) to save money. It’s a very different mindset.
theCUBE’s next stop is the Hilton Santa Clara for #BigDataSV. The show takes place February 11-13, 2014 and you can catch all the action live at SiliconANGLE.tv. We’ll have analysis of all the news breaking at Strata Conference, as well as in-depth conversations with leading Big Data and Data Science thought-leaders.
In addition to the broadcast, we’re also throwing a little soiree the evening of February 12 at the Hilton. If you’re attending Strata, please joins us between 6pm-8pm PST in the Coastal Room for some drinks and hors d’oeuvres and socializing. RSVP here.
I’ve already laid out my predictions for Big Data in 2014, but I also wanted to let the Wikibon community know how my colleagues and I plan to cover Big Data in the year ahead. We’ve organized our research agenda into three major buckets.
Technology. Clearly the technologies and products that collectively make up Big Data – including Hadoop, NoSQL data stores, analytic databases, data visualization tools and more – are maturing at a rapid pace (much faster, for example, than relational databases did in the 1980s.) Big Data is also applicable across industries, meaning these technologies are inevitably and increasingly intersecting with adjacent technology movements, namely the cloud, mobile computing and social media. As we have for the last several years, Wikibon will devote significant coverage to these developments with an eye on putting technology innovations in context for enterprise Big Data practitioners (both technology practitioners and line-of-business practitioners.)