Click here to close now.

Welcome!

Big Data Journal Authors: Pat Romanski, Elizabeth White, Carmen Gonzalez, John Wetherill, Liz McMillan

Related Topics: Big Data Journal, Java, Microservices Journal, Virtualization, Cloud Expo, SDN Journal

Big Data Journal: Article

Archiving the Big Data Old Tail

At any point in time, half of your Big Data are more than two years old

Scenario #1: out of the blue, your boss calls, looking for some long-forgotten entry in a spreadsheet from 1989. Where do you look? Or consider scenario #2: said boss calls again, only this time she wants you to analyze customer purchasing behavior...going back to 1980. Similar problem, only instead of finding a single datum, you must find years of ancient information and prepare it for analysis with a modern business intelligence tool.

The answer, of course, is archiving. Fortunately, you (or your predecessor, or predecessor's predecessor) have been archiving important-or potentially important-corporate data since your organization first started using computers back in the 1960s. So all you have to do to keep your boss happy is find the appropriate archives, recover the necessary data, and you're good to go, right?

Not so fast. There are a number of gotchas to this story, some more obvious than others. Cloud to the rescue? Perhaps, but many archiving challenges remain, and the Cloud actually introduces some new speed bumps as well. Now factor in Big Data. Sure, Big Data are big, so archiving Big Data requires a big archive. Lucky you-vendors have already been knocking on your door peddling Big Data archiving solutions. Now can you finally breathe easy? Maybe, maybe not. Here's why.

Archiving: The Long View
So much of our digital lives have taken place over the last twenty years or so that we forget that digital computing dates back to the 1940s-and furthermore, we forget that this sixty-odd year lifetime of the Information Age is really only the first act of perhaps centuries of computing before humankind either evolves past zeroes and ones altogether or kills itself off in the process. Our technologies for archiving information, however, are woefully shortsighted, for several reasons:

  • Hardware obsolescence (three to five years) - Using a hard drive or tape drive for archiving? It won't be long till the hardware is obsolete. You may get more life out of the gear you own, but one it wears out, you'll be stuck. Anyone who archived to laser disk in the 1980s has been down this road.
  • File format obsolescence (five to ten years) - True, today's Office products can probably read that file originally saved in the Microsoft Excel version 1 file format back in the day, but what about those VisiCalc or Lotus 123 files? Tools that will convert such files to their modern equivalents will eventually grow increasingly scarce, and you always risk the possibility that they won't handle the conversion properly, leading to data corruption. If your data are encrypted, then your encryption format falls into the file format obsolescence bucket as well. And what about the programs themselves? From simple spreadsheet formulas to complex legacy spaghetti code, how do you archive algorithms in an obsolescence-proof format?
  • Media obsolescence (ten to fifteen years) - CD-ROMs and digital backup tapes have an expected lifetime. Keeping them cool and dry can extend their life, but actually using them will shorten it. Do you really want to rely upon a fifteen-year-old backup tape for critical information?
  • Computing paradigm obsolescence (fifty years perhaps; it's anybody's guess) - will quantum computing or biological processors or some other futuristic gear drive binary digital technologies into the Stone Age? Only time will tell. But if you are forward thinking enough to archive information for the 22nd century, there's no telling what you'll need to do to maintain the viability of your archives in a post-binary world.

Cloud to the Rescue?
On the surface, letting your Cloud Service Provider (CSP) archive your data solves many of these issues. Not only are the new archiving services like Amazon Glacier impressively cost-effective, but we can feel reasonably comfortable counting on today's CSPs to migrate our data from one hardware/media platform to the next over time as technology advances. So, can Cloud solve all your archiving issues?

At some point the answer may be yes, but Cloud Computing is still far too immature to jump to such a conclusion. Will your CSP still be in business decades from now? As the CSP market undergoes its inevitable consolidation phase, will the new CSP who bought out your old CSP handle your archive properly? Only time will tell.

But even if the CSPs rise to the archiving challenge, you may still have the file format challenge. Sure, archiving those old Lotus 123 files in the Cloud is a piece of cake, but that doesn't mean that your CSP will return them in Excel version 21.3 format ten years hence-an unfortunate and unintentional example of garbage in the Cloud.

The Big Data Old Tail
You might think that the challenges inherent in archiving Big Data are simply a matter of degree: bigger storage for bigger data sets, right? But thinking of Big Data as little more than extra-large data sets misses the big picture of the importance of Big Data.

The point to Big Data is that the indicated data sets continue to grow in size on an ongoing basis, continually pushing the limits of existing technology. The more capacity available for storage and processing, the larger the data sets we end up with. In other words, Big Data are by definition a moving target.

One familiar estimate states that the quantity of data in the world doubles every two years. Your organization's Big Data may grow somewhat faster or slower than this convenient benchmark, but in any case, the point is that Big Data growth is exponential. So, taking the two-year doubling factor as a rule of thumb, we can safely say that at any point in time, half of your Big Data are less than two years old, while the other half of your Big Data are more than two years old. And of course, this ZapFlash is concerned with the older half.

The Big Data archiving challenge, therefore, is breaking down the more-than-two-years-old Big Data sets. Remember that this two-year window is true at any point in time. Thinking about the problem mathematically, then, you can conclude that a quarter of your Big Data are more than four years old, an eighth are more than six years old, etc.

Combine this math with the lesson of the first part of this ZapFlash, and a critical point emerges: byte for byte, the cost of maintaining usable archives increases the older those archives become. And yet, the relative size of those archives is vanishingly small relative to today's and tomorrow's Big Data. Furthermore, this problem will only get worse over time, because the size of the Old Tail continues to grow exponentially.

We call this Big Data archiving problem the Big Data Old Tail. Similar to the Long Tail argument, which focuses on the value inherent in summing up the Long Tail of customer demand for niche products, the Big Data Old Tail focuses on the costs inherent in maintaining archives of increasingly small, yet increasingly costly data as we struggle to deal with older and older information. True, perhaps the fact that the Old Tail data sets from a particular time period are small will compensate for the fact that they are costly to archive, but remember that the Old Tail continues to grow over time. Unless we deal with the Old Tail, it threatens to overwhelm us.

The ZapThink Take
The obvious question that comes to mind is whether we need to save all those old data sets anyway. After all, who cares about, say, purchasing data from 1982? And of course, you may have a business reason for deleting old information. Since information you preserve may be subject to lawsuits or other unpleasantness, you may wish to delete data once it's legal to do so.

Fair enough. But there are perhaps far more examples of Big Data sets that your organization will wish to preserve indefinitely than data sets you're happy to delete. From scientific data to information on market behavior to social trends, the richness of our Big Data do not simply depend on the information from the last year or two or even ten. After all, if we forget the mistakes of the past then we are doomed to repeat them. Crunching today's Big Data can give us business intelligence, but only by crunching yesterday's Big Data as well can we ever expect to glean wisdom from our information.

More Stories By Jason Bloomberg

Jason Bloomberg is the leading expert on architecting agility for the enterprise. As president of Intellyx, Mr. Bloomberg brings his years of thought leadership in the areas of Cloud Computing, Enterprise Architecture, and Service-Oriented Architecture to a global clientele of business executives, architects, software vendors, and Cloud service providers looking to achieve technology-enabled business agility across their organizations and for their customers. His latest book, The Agile Architecture Revolution (John Wiley & Sons, 2013), sets the stage for Mr. Bloomberg’s groundbreaking Agile Architecture vision.

Mr. Bloomberg is perhaps best known for his twelve years at ZapThink, where he created and delivered the Licensed ZapThink Architect (LZA) SOA course and associated credential, certifying over 1,700 professionals worldwide. He is one of the original Managing Partners of ZapThink LLC, the leading SOA advisory and analysis firm, which was acquired by Dovel Technologies in 2011. He now runs the successor to the LZA program, the Bloomberg Agile Architecture Course, around the world.

Mr. Bloomberg is a frequent conference speaker and prolific writer. He has published over 500 articles, spoken at over 300 conferences, Webinars, and other events, and has been quoted in the press over 1,400 times as the leading expert on agile approaches to architecture in the enterprise.

Mr. Bloomberg’s previous book, Service Orient or Be Doomed! How Service Orientation Will Change Your Business (John Wiley & Sons, 2006, coauthored with Ron Schmelzer), is recognized as the leading business book on Service Orientation. He also co-authored the books XML and Web Services Unleashed (SAMS Publishing, 2002), and Web Page Scripting Techniques (Hayden Books, 1996).

Prior to ZapThink, Mr. Bloomberg built a diverse background in eBusiness technology management and industry analysis, including serving as a senior analyst in IDC’s eBusiness Advisory group, as well as holding eBusiness management positions at USWeb/CKS (later marchFIRST) and WaveBend Solutions (now Hitachi Consulting).

@BigDataExpo Stories
The Internet of Things (IoT) promises to evolve the way the world does business; however, understanding how to apply it to your company can be a mystery. Most people struggle with understanding the potential business uses or tend to get caught up in the technology, resulting in solutions that fail to meet even minimum business goals. In his session at @ThingsExpo, Jesse Shiah, CEO / President / Co-Founder of AgilePoint Inc., showed what is needed to leverage the IoT to transform your business. ...
In his session at DevOps Summit, Tapabrata Pal, Director of Enterprise Architecture at Capital One, will tell a story about how Capital One has embraced Agile and DevOps Security practices across the Enterprise – driven by Enterprise Architecture; bringing in Development, Operations and Information Security organizations together. Capital Ones DevOpsSec practice is based upon three "pillars" – Shift-Left, Automate Everything, Dashboard Everything. Within about three years, from 100% waterfall, C...
With the arrival of the Big Data revolution, a data professional is expected to master a broad spectrum of complex domains including data processing, mathematics, programming languages, machine learning techniques, and business knowledge. While this mastery is undoubtedly important, this narrow focus on tool usage has divorced many from the imagination required to solve real-world problems. As the demand for analysis increases, the data science community must transform from tool experts to "data...
Thanks to Docker, it becomes very easy to leverage containers to build, ship, and run any Linux application on any kind of infrastructure. Docker is particularly helpful for microservice architectures because their successful implementation relies on a fast, efficient deployment mechanism – which is precisely one of the features of Docker. Microservice architectures are therefore becoming more popular, and are increasingly seen as an interesting option even for smaller projects, instead of bein...
DevOps tends to focus on the relationship between Dev and Ops, putting an emphasis on the ops and application infrastructure. But that’s changing with microservices architectures. In her session at DevOps Summit, Lori MacVittie, Evangelist for F5 Networks, will focus on how microservices are changing the underlying architectures needed to scale, secure and deliver applications based on highly distributed (micro) services and why that means an expansion into “the network” for DevOps.
We’re no longer looking to the future for the IoT wave. It’s no longer a distant dream but a reality that has arrived. It’s now time to make sure the industry is in alignment to meet the IoT growing pains – cooperate and collaborate as well as innovate. In his session at @ThingsExpo, Jim Hunter, Chief Scientist & Technology Evangelist at Greenwave Systems, will examine the key ingredients to IoT success and identify solutions to challenges the industry is facing. The deep industry expertise be...
The 3rd International @ThingsExpo, co-located with the 16th International Cloud Expo – to be held June 9-11, 2015, at the Javits Center in New York City, NY – is now accepting Hackathon proposals. Hackathon sponsorship benefits include general brand exposure and increasing engagement with the developer ecosystem. At Cloud Expo 2014 Silicon Valley, IBM held the Bluemix Developer Playground on November 5 and ElasticBox held the DevOps Hackathon on November 6. Both events took place on the expo fl...
In his session at DevOps Summit, Tapabrata Pal, Director of Enterprise Architecture at Capital One, will tell a story about how Capital One has embraced Agile and DevOps Security practices across the Enterprise – driven by Enterprise Architecture; bringing in Development, Operations and Information Security organizations together. Capital Ones DevOpsSec practice is based upon three "pillars" – Shift-Left, Automate Everything, Dashboard Everything. Within about three years, from 100% waterfall, C...
As enterprises look to take advantage of the cloud, they need to understand the importance of safeguarding their confidential and sensitive data in cloud environments. Enterprises must protect their data from (i) system administrators who don't need to see the data in the clear and (ii) adversaries who become system administrators from stolen credentials. In short, enterprises must take control of their data: The best way to do this is by using advanced encryption, centralized key management and...
A new definition of Big Data & the practical applications of the defined components & associated technical architecture models This presentation introduces a new definition of Big Data, along with the practical applications of the defined components and associated technical architecture models. In his session at Big Data Expo, Tony Shan will start with looking into the concept of Big Data and tracing back the first definition by Doug Laney, and then he will dive deep into the description of 3V...
SYS-CON Events announced today that Gridstore™, the leader in hyper-converged infrastructure purpose-built to optimize Microsoft workloads, will exhibit at SYS-CON's 16th International Cloud Expo®, which will take place on June 9-11, 2015, at the Javits Center in New York City, NY. Gridstore™ is the leader in hyper-converged infrastructure purpose-built for Microsoft workloads and designed to accelerate applications in virtualized environments. Gridstore’s hyper-converged infrastructure is the ...
Cryptography has become one of the most underappreciated, misunderstood components of technology. It’s too easy for salespeople to dismiss concerns with three letters that nobody wants to question. ‘Yes, of course, we use AES.’ But what exactly are you trusting to be the ultimate guardian of your data? Let’s face it – you probably don’t know. An organic, grass-fed Kobe steak is a far cry from a Big Mac, but they’re both beef, right? Not exactly. Crypto is the same way. The US government require...
of cloud, colocation, managed services and disaster recovery solutions, will exhibit at SYS-CON's 16th International Cloud Expo®, which will take place on June 9-11, 2015, at the Javits Center in New York City, NY. TierPoint, LLC, is a leading national provider of information technology and data center services, including cloud, colocation, disaster recovery and managed IT services, with corporate headquarters in St. Louis, MO. TierPoint was formed through the strategic combination of some of t...
Hadoop as a Service (as offered by handful of niche vendors now) is a cloud computing solution that makes medium and large-scale data processing accessible, easy, fast and inexpensive. In his session at Big Data Expo, Kumar Ramamurthy, Vice President and Chief Technologist, EIM & Big Data, at Virtusa, will discuss how this is achieved by eliminating the operational challenges of running Hadoop, so one can focus on business growth. The fragmented Hadoop distribution world and various PaaS soluti...
With major technology companies and startups seriously embracing IoT strategies, now is the perfect time to attend @ThingsExpo in Silicon Valley. Learn what is going on, contribute to the discussions, and ensure that your enterprise is as "IoT-Ready" as it can be! Internet of @ThingsExpo, taking place Nov 3-5, 2015, at the Santa Clara Convention Center in Santa Clara, CA, is co-located with 17th Cloud Expo and will feature technical sessions from a rock star conference faculty and the leading in...
Cultural, regulatory, environmental, political and economic (CREPE) conditions over the past decade are creating cross-industry solution spaces that require processes and technologies from both the Internet of Things (IoT), and Data Management and Analytics (DMA). These solution spaces are evolving into Sensor Analytics Ecosystems (SAE) that represent significant new opportunities for organizations of all types. Public Utilities throughout the world, providing electricity, natural gas and water,...
All major researchers estimate there will be tens of billions devices - computers, smartphones, tablets, and sensors - connected to the Internet by 2020. This number will continue to grow at a rapid pace for the next several decades. With major technology companies and startups seriously embracing IoT strategies, now is the perfect time to attend @ThingsExpo, June 9-11, 2015, at the Javits Center in New York City. Learn what is going on, contribute to the discussions, and ensure that your enter...
The true value of the Internet of Things (IoT) lies not just in the data, but through the services that protect the data, perform the analysis and present findings in a usable way. With many IoT elements rooted in traditional IT components, Big Data and IoT isn’t just a play for enterprise. In fact, the IoT presents SMBs with the prospect of launching entirely new activities and exploring innovative areas. CompTIA research identifies several areas where IoT is expected to have the greatest impac...
There is little doubt that Big Data solutions will have an increasing role in the Enterprise IT mainstream over time. 8th International Big Data Expo, co-located with 17th International Cloud Expo - to be held November 3-5, 2015, at the Santa Clara Convention Center in Santa Clara, CA - has announced its Call for Papers is open. As advanced data storage, access and analytics technologies aimed at handling high-volume and/or fast moving data all move center stage, aided by the cloud computing bo...
Every day we read jaw-dropping stats on the explosion of data. We allocate significant resources to harness and better understand it. We build businesses around it. But we’ve only just begun. For big payoffs in Big Data, CIOs are turning to cognitive computing. Cognitive computing’s ability to securely extract insights, understand natural language, and get smarter each time it’s used is the next, logical step for Big Data.