|By Greg Schulz||
|November 1, 2012 09:00 AM EDT||
This is an industry trends and perspective piece about big data and little data, industry adoption and customer deployment.
If you are in any way associated with information technology (IT), business, scientific, media and entertainment computing or related areas, you may have heard big data mentioned. Big data has been a popular buzzword bingo topic and term for a couple of years now. Big data is being used to describe new and emerging along with existing types of applications and information processing tools and techniques.
I routinely hear from different people or groups trying to define what is or is not big data and all too often those are based on a particular product, technology, service or application focus. Thus it should be no surprise that those trying to police what is or is not big data will often do so based on what their interest, sphere of influence, knowledge or experience and jobs depend on.
Not long ago while out traveling I ran into a person who told me that big data is new data that did not exist just a few years ago. Turns out this person was involved in geology so I was surprised that somebody in that field was not aware of or working with geophysical, mapping, seismic and other legacy or traditional big data. Turns out this person was basing his statements on what he knew, heard, was told about or on sphere of influence around a particular technology, tool or approach.
Fwiw, if you have not figured out already, like cloud, virtualization and other technology enabling tools and techniques, I tend to take a pragmatic approach vs. becoming latched on to a particular bandwagon (for or against) per say.
Not surprisingly there is confusion and debate about what is or is not big data including if it only applies to new vs. existing and old data. As with any new technology, technique or buzzword bingo topic theme, various parties will try to place what is or is not under the definition to align with their needs, goals and preferences. This is the case with big data where you can routinely find proponents of Hadoop and Map reduce position big data as aligning with the capabilities and usage scenarios of those related technologies for business and other forms of analytics.
Not surprisingly the granddaddy of all business analytics, data science and statistic analysis number crunching is the Statistical Analysis Software (SAS) from the SAS Institute. If these types of technology solutions and their peers define what is big data then SAS (not to be confused with Serial Attached SCSI which can be found on the back-end of big data storage solutions) can be considered first generation big data analytics or Big Data 1.0 (BD1 ;) ). That means Hadoop Map Reduce is Big Data 2.0 (BD2 ;) ;) ) if you like, or dislike for that matter.
Funny thing about some fans and proponents or surrogates of BD2 is that they may have heard of BD1 like SAS with a limited understanding of what it is or how it is or can be used. When I worked in IT as a performance and capacity planning analyst focused on servers, storage, network hardware, software and applications I used SAS to crunch various data streams of event, activity and other data from diverse sources. This involved correlating data, running various analytic algorithms on the data to determine response times, availability, usage and other things in support of modeling, forecasting, tuning and trouble shooting. Hmm, sound like first generation big data analytics or Data Center Infrastructure Management (DCIM) and IT Service Management (ITSM) to anybody?
Now to be fair, comparing SAS, SPSS or any number of other BD1 generation tools to Hadoop and Map Reduce or BD2 second generation tools is like comparing apples to oranges, or apples to pears. Lets move on as there is much more to what is big data than simply focus around SAS or Hadoop.
Another type of big data are the information generated, processed, stored and used by applications that result in large files, data sets or objects. Large file, objects or data sets include low resolution and high-definition photos, videos, audio, security and surveillance, geophysical mapping and seismic exploration among others. Then there are data warehouses where transactional data from databases gets moved to for analysis in systems such as those from Oracle, Teradata, Vertica or FX among others. Some of those other tools even play (or work) in both traditional e.g. BD1 and new or emerging BD2 worlds.
This is where some interesting discussions, debates or disagreements can occur between those who latch onto or want to keep big data associated with being something new and usually focused around their preferred tool or technology. What results from these types of debates or disagreements is a missed opportunity for organizations to realize that they might already be doing or using a form of big data and thus have a familiarity and comfort zone with it.
By having a familiarity or comfort zone vs. seeing big data as something new, different, hype or full of FUD (or BS), an organization can be comfortable with the term big data. Often after taking a step back and looking at big data beyond the hype or fud, the reaction is along the lines of, oh yeah, now we get it, sure, we are already doing something like that so lets take a look at some of the new tools and techniques to see how we can extend what we are doing.
Likewise many organizations are doing big bandwidth already and may not realize it thinking that is only what media and entertainment, government, technical or scientific computing, high performance computing or high productivity computing (HPC) does. I'm assuming that some of the big data and big bandwidth pundits will disagree, however if in your environment you are doing many large backups, archives, content distribution, or copying large amounts of data for different purposes that consume big bandwidth and need big bandwidth solutions.
Yes I know, that's apples to oranges and perhaps stretching the limits of what is or can be called big bandwidth based on somebody's definition, taxonomy or preference. Hopefully you get the point that there is diversity across various environments as well as types of data and applications, technologies, tools and techniques.
What about little data then?
I often say that if big data is getting all the marketing dollars to generate industry adoption, then little data is generating all the revenue (and profit or margin) dollars by customer deployment. While tools and technologies related to Hadoop (or Haydoop if you are from HDS) are getting industry adoption attention (e.g. marketing dollars being spent) revenues from customer deployment are growing.
Where big data revenues are strongest for most vendors today are centered around solutions for hosting, storing, managing and protecting big files, big objects. These include scale out NAS solutions for large unstructured data like those from Amplidata, Cray, Dell, Data Direct Networks (DDN), EMC (e.g. Isilon), HP X9000 (IBRIX), IBM SONAS, NetApp, Oracle and Xyratex among others. Then there flexible converged compute storage platforms optimized for analytics and running different software tools such as those from EMC (Greenplum), IBM (Netezza), NetApp (via partnerships) or Oracle among others that can be used for different purposes in addition to supporting Hadoop and Map reduce.
If little data is databases and things not generally lumped into the big data bucket, and if you think or perceive big data only to be Hadoop map reduce based data, then does that mean all the large unstructured non little data is then very big data or VBD?
Of course the virtualization folks might want to if they have not already corner the V for Virtual Big Data. In that case, then instead of Very Big Data, how about very very Big Data (vvBD). How about Ultra-Large Big Data (ULBD), or High-Revenue Big Data (HRBD), granted the HR might cause some to think its unique for Health Records, or Human Resources, both btw leverage different forms of big data regardless of what you see or think big data is.
Does that then mean we should really be calling videos, audio, PACs, seismic, security surveillance video and related data to be VBD? Would this further confuse the market, or the industry or help elevate it to a grander status in terms of size (data file or object capacity, bandwidth, market size and application usage, market revenue and so forth)?
Do we need various industry consortiums, lobbyists or trade groups to go off and create models, taxonomies, standards and dictionaries based on their constituents needs and would they align with those of the customers, after all, there are big dollars flowing around big data industry adoption (marketing).
What does this all mean?
Is Big Data BS?
First let me be clear, big data is not BS, however there is a lot of BS marketing BS by some along with hype and fud adding to the confusion and chaos, perhaps even missed opportunities. Keep in mind that in chaos and confusion there can be opportunity for some.
IMHO big data is real.
There are different variations, use cases and types of products, technologies and services that fall under the big data umbrella. That does not mean everything can or should fall under the big data umbrella as there is also little data.
What this all means is that there are different types of applications for various industries that have big and little data, virtual and very big data from videos, photos, images, audio, documents and more.
Big data is a big buzzword bingo term these days with vendor marketing big dollars being applied so no surprise the buzz, hype, fud and more.
Ok, nuff said, for now...
All Comments, (C) and (TM) belong to their owners/posters, Other content (C) Copyright 2006-2012 StorageIO All Rights Reserved
Somebody call the buzzword police: we have a serious case of microservices-washing in progress. The term “microservices-washing” is derived from “whitewashing,” meaning to hide some inconvenient truth with bluster and nonsense. We saw plenty of cloudwashing a few years ago, as vendors and enterprises alike pretended what they were doing was cloud, even though it wasn’t. Today, the hype around microservices has led to the same kind of obfuscation, as vendors and enterprise technologists alike ar...
Oct. 7, 2015 12:00 AM EDT Reads: 375
SYS-CON Events announced today that G2G3 will exhibit at SYS-CON's @DevOpsSummit Silicon Valley, which will take place on November 3–5, 2015, at the Santa Clara Convention Center in Santa Clara, CA. Based on a collective appreciation for user experience, design, and technology, G2G3 is uniquely qualified and motivated to redefine how organizations and people engage in an increasingly digital world.
Oct. 6, 2015 11:15 PM EDT Reads: 357
If you are new to Python, you might be confused about the different versions that are available. Although Python 3 is the latest generation of the language, many programmers still use Python 2.7, the final update to Python 2, which was released in 2010. There is currently no clear-cut answer to the question of which version of Python you should use; the decision depends on what you want to achieve. While Python 3 is clearly the future of the language, some programmers choose to remain with Py...
Oct. 6, 2015 08:00 PM EDT Reads: 187
“All our customers are looking at the cloud ecosystem as an important part of their overall product strategy. Some see it evolve as a multi-cloud / hybrid cloud strategy, while others are embracing all forms of cloud offerings like PaaS, IaaS and SaaS in their solutions,” noted Suhas Joshi, Vice President – Technology, at Harbinger Group, in this exclusive Q&A with Cloud Expo Conference Chair Roger Strukhoff.
Oct. 6, 2015 02:45 PM EDT Reads: 373
Opinions on how best to package and deliver applications are legion and, like many other aspects of the software world, are subject to recurring trend cycles. On the server-side, the current favorite is container delivery: a “full stack” approach in which your application and everything it needs to run are specified in a container definition. That definition is then “compiled” down to a container image and deployed by retrieving the image and passing it to a container runtime to create a running...
Oct. 6, 2015 12:45 PM EDT Reads: 135
Clearly the way forward is to move to cloud be it bare metal, VMs or containers. One aspect of the current public clouds that is slowing this cloud migration is cloud lock-in. Every cloud vendor is trying to make it very difficult to move out once a customer has chosen their cloud. In his session at 17th Cloud Expo, Naveen Nimmu, CEO of Clouber, Inc., will advocate that making the inter-cloud migration as simple as changing airlines would help the entire industry to quickly adopt the cloud wit...
Oct. 6, 2015 12:30 PM EDT Reads: 588
As the world moves towards more DevOps and microservices, application deployment to the cloud ought to become a lot simpler. The microservices architecture, which is the basis of many new age distributed systems such as OpenStack, NetFlix and so on, is at the heart of Cloud Foundry - a complete developer-oriented Platform as a Service (PaaS) that is IaaS agnostic and supports vCloud, OpenStack and AWS. In his session at 17th Cloud Expo, Raghavan "Rags" Srinivas, an Architect/Developer Evangeli...
Oct. 6, 2015 12:15 PM EDT Reads: 114
Culture is the most important ingredient of DevOps. The challenge for most organizations is defining and communicating a vision of beneficial DevOps culture for their organizations, and then facilitating the changes needed to achieve that. Often this comes down to an ability to provide true leadership. As a CIO, are your direct reports IT managers or are they IT leaders? The hard truth is that many IT managers have risen through the ranks based on their technical skills, not their leadership ab...
Oct. 6, 2015 11:00 AM EDT Reads: 854
Apps and devices shouldn't stop working when there's limited or no network connectivity. Learn how to bring data stored in a cloud database to the edge of the network (and back again) whenever an Internet connection is available. In his session at 17th Cloud Expo, Bradley Holt, Developer Advocate at IBM Cloud Data Services, will demonstrate techniques for replicating cloud databases with devices in order to build offline-first mobile or Internet of Things (IoT) apps that can provide a better, ...
Oct. 6, 2015 10:45 AM EDT Reads: 455
Despite all the talk about public cloud services and DevOps, you would think the move to cloud for enterprises is clear and simple. But in a survey of almost 1,600 IT decision makers across the USA and Europe, the state of the cloud in enterprise today is still fraught with considerable frustration. The business case for apps in the real world cloud is hybrid, bimodal, multi-platform, and difficult. Download this report commissioned by NTT Communications to see the insightful findings – registra...
Oct. 6, 2015 10:00 AM EDT Reads: 218
Application availability is not just the measure of “being up”. Many apps can claim that status. Technically they are running and responding to requests, but at a rate which users would certainly interpret as being down. That’s because excessive load times can (and will be) interpreted as “not available.” That’s why it’s important to view ensuring application availability as requiring attention to all its composite parts: scalability, performance, and security.
Oct. 6, 2015 09:00 AM EDT Reads: 355
SYS-CON Events announced today that HPM Networks will exhibit at the 17th International Cloud Expo®, which will take place on November 3–5, 2015, at the Santa Clara Convention Center in Santa Clara, CA. For 20 years, HPM Networks has been integrating technology solutions that solve complex business challenges. HPM Networks has designed solutions for both SMB and enterprise customers throughout the San Francisco Bay Area.
Oct. 6, 2015 09:00 AM EDT Reads: 573
There once was a time when testers operated on their own, in isolation. They’d huddle as a group around the harsh glow of dozens of CRT monitors, clicking through GUIs and recording results. Anxiously, they’d wait for the developers in the other room to fix the bugs they found, yet they’d frequently leave the office disappointed as issues were filed away as non-critical. These teams would rarely interact, save for those scarce moments when a coder would wander in needing to reproduce a particula...
Oct. 6, 2015 08:45 AM EDT Reads: 261
What Is Emergent About Emergent Architecture? By @TheEbizWizard | @DevOpsSummit #DevOps #BigData #API
All we need to do is have our teams self-organize, and behold! Emergent design and/or architecture springs up out of the nothingness! If only it were that easy, right? I follow in the footsteps of so many people who have long wondered at the meanings of such simple words, as though they were dogma from on high. Emerge? Self-organizing? Profound, to be sure. But what do we really make of this sentence?
Oct. 6, 2015 08:00 AM EDT Reads: 382
As we increasingly rely on technology to improve the quality and efficiency of our personal and professional lives, software has become the key business differentiator. Organizations must release software faster, as well as ensure the safety, security, and reliability of their applications. The option to make trade-offs between time and quality no longer exists—software teams must deliver quality and speed. To meet these expectations, businesses have shifted from more traditional approaches of d...
Oct. 6, 2015 07:45 AM EDT Reads: 158
Information overload has infiltrated our lives. From the amount of news available and at our fingertips 24/7, to the endless choices we have when making a simple purchase, to the quantity of emails we receive on a given day, it’s increasingly difficult to sift out the details that really matter. When you envision your cloud monitoring system, the same thinking applies. We receive a lot of useless data that gets fed into the system, and the reality is no one in IT or DevOps has the time to manu...
Oct. 6, 2015 07:00 AM EDT Reads: 499
Last month, my partners in crime – Carmen DeArdo from Nationwide, Lee Reid, my colleague from IBM and I wrote a 3-part series of blog posts on DevOps.com. We titled our posts the Simple Math, Calculus and Art of DevOps. I would venture to say these are must-reads for any organization adopting DevOps. We examined all three ascpects – the Cultural, Automation and Process improvement side of DevOps. One of the key underlying themes of the three posts was the need for Cultural change – things like t...
Oct. 6, 2015 04:15 AM EDT Reads: 278
It is with great pleasure that I am able to announce that Jesse Proudman, Blue Box CTO, has been appointed to the position of IBM Distinguished Engineer. Jesse is the first employee at Blue Box to receive this honor, and I’m quite confident there will be more to follow given the amazing talent at Blue Box with whom I have had the pleasure to collaborate. I’d like to provide an overview of what it means to become an IBM Distinguished Engineer.
Oct. 6, 2015 03:45 AM EDT Reads: 141
I’ve been thinking a bit about microservices (μServices) recently. My immediate reaction is to think: “Isn’t this just yet another new term for the same stuff, Web Services->SOA->APIs->Microservices?” Followed shortly by the thought, “well yes it is, but there are some important differences/distinguishing factors.” Microservices is an evolutionary paradigm born out of the need for simplicity (i.e., get away from the ESB) and alignment with agile (think DevOps) and scalable (think Containerizati...
Oct. 6, 2015 03:00 AM EDT Reads: 2,460
The cloud has reached mainstream IT. Those 18.7 million data centers out there (server closets to corporate data centers to colocation deployments) are moving to the cloud. In his session at 17th Cloud Expo, Achim Weiss, CEO & co-founder of ProfitBricks, will share how two companies – one in the U.S. and one in Germany – are achieving their goals with cloud infrastructure. More than a case study, he will share the details of how they prioritized their cloud computing infrastructure deployments ...
Oct. 6, 2015 03:00 AM EDT Reads: 683