|By Tim Negris||
|February 7, 2014 11:00 AM EST||
The settling of the American West brought many battles between ranchers and farmers over access to water. The farmers claimed land near the water and fenced it to protect their crops. But the farmers' fences blocked the ranchers' cattle from reaching the water. Fences were cut; shots were fired; it got ugly.
About a century later, with the first tech land rush of the late1980s and early '90s - before the Web - came battles between those who wanted software and data to be centrally controlled on corporate servers and those who wanted it to be distributed to workers' desktops. Oracle and IBM versus Microsoft and Lotus. Database versus Spreadsheet.
Now, with the advent of SoMoClo (Social, Mobile, Cloud) technologies and the Big Data they create, have come battles between groups on different sides of the "Data Lake" over how it should be controlled, managed, used, and paid for. Operations versus Strategy. BI versus Data Science. Governance versus Discovery. Oversight versus Insight.
The range wars of the Old West were not a fight over property ownership, but rather over access to natural resources. The farmers and their fences won that one, for the most part.
Those tech battles in the enterprise are fights over access to the "natural" resource of data and to the tools for managing and analyzing it.
In the '90s and most of the following decade, the farmers won again. Data was harvested from corporate systems and piled high in warehouses, with controlled accessed by selected users for milling it into Business Intelligence.
But now in the era of Big Data Analytics, it is not looking so good for the farmers. The public cloud, open source databases, and mobile tablets are all chipping away at the centralized command-and-control infrastructure down by the riverside. And, new cloud based Big Data analytics solution providers like BigML, Yottamine (my company) and others are putting unprecedented analytical power in the hands of the data ranchers.
A Rainstorm, Not a River
Corporate data is like a river - fed by transaction tributaries and dammed into databases for controlled use in business irrigation.
Big Data is more like a relentless rainstorm - falling heavily from the cloud and flowing freely over and around corporate boundaries, with small amounts channeled into analytics and most draining to the digital deep.
Many large companies are failing to master this new data ecology because they are trying to do Big Data analytics in the same way, with the same tools as they did with BI, and that will never work. There is a lot more data, of course, but it is different data - tweets, posts, pictures, clicks, GPS, etc., not RDBMS records - and different analytics - discovery and prediction, not reporting and evaluation.
Successfully gleaning business value from the Big Data rainstorm requires new tools and maybe new rules.
These days, tech industry content readers frequently see the term "Shadow IT" referring to how business people are using new technologies to process and analyze information without the help of "real IT". SoMoClo by another, more sinister name. Traditionalists see it as a threat to corporate security and stability and modernists a boon to cost control and competitiveness.
But, it really doesn't matter which view is right. Advanced analytics on Big Data takes more computing horsepower than most companies can afford. Jobs like machine learning from the Twitter Fire Hose will take hundreds or even thousands of processor cores and terabytes of memory (not disk!) to build accurate and timely predictive models.
Most companies will have no choice but to embrace the shadow and use AWS or some other elastic cloud computing service, and new, more scalable software tools to do effective large scale advanced analytics.
Time for New Rules?
Advanced Big Data analytics projects, the ones of a scale that only the cloud can handle, are being held back by reservations over privacy, security and liability that in most cases turn out to be needless concerns.
If the data to be analyzed were actual business records for customers and transactions as it is in the BI world, those concerns would be reasonable. But more often than not, advanced analytics does not work that way. Machine learning and other advanced algorithms do not look at business data. They look at statistical information derived from business data, usually in the form of an inscrutable mass of binary truth values that is only actionable to the algorithm. That is what gets sent to the cloud, not the customer file.
If you want to do advanced cloud-scale Big Data analytics and somebody is telling you it is against the rules, you should look at the rules. They probably don't even apply to what you are trying to do.
First User Advantage
Advanced Big Data analytics is sufficiently new and difficult that not many companies are doing much of it yet. But where BI helps you run a tighter ship, Big Data analytics helps you sink your enemy's fleet.
Some day, technologies like high performance statistical machine learning will be ubiquitous and the business winners will be the ones who uses the software best. But right now, solutions are still scarce and the business winners are ones willing to use the software at all.
Technology vendors and analysts are eager to paint a rosy picture of how wonderful IoT is and why your deployment will be great with the use of their products and services. While it is easy to showcase successful IoT solutions, identifying IoT systems that missed the mark or failed can often provide more in the way of key lessons learned. In his session at @ThingsExpo, Peter Vanderminden, Principal Industry Analyst for IoT & Digital Supply Chain to Flatiron Strategies, will focus on how IoT de...
Sep. 28, 2016 08:30 AM EDT Reads: 1,147
In his session at @ThingsExpo, Kausik Sridharabalan, founder and CTO of Pulzze Systems, Inc., will focus on key challenges in building an Internet of Things solution infrastructure. He will shed light on efficient ways of defining interactions within IoT solutions, leading to cost and time reduction. He will also introduce ways to handle data and how one can develop IoT solutions that are lean, flexible and configurable, thus making IoT infrastructure agile and scalable.
Sep. 28, 2016 08:30 AM EDT Reads: 1,564
Complete Internet of Things (IoT) embedded device security is not just about the device but involves the entire product’s identity, data and control integrity, and services traversing the cloud. A device can no longer be looked at as an island; it is a part of a system. In fact, given the cross-domain interactions enabled by IoT it could be a part of many systems. Also, depending on where the device is deployed, for example, in the office building versus a factory floor or oil field, security ha...
Sep. 28, 2016 08:15 AM EDT Reads: 534
"We have several customers now running private clouds. They're not as large as they should be but it's getting there. The adoption challenge has been pretty simple. Look at the world today of virtualization vs cloud," stated Nara Rajagopalan, CEO of Accelerite, in this SYS-CON.tv interview at 18th Cloud Expo, held June 7-9, 2016, at the Javits Center in New York City, NY.
Sep. 28, 2016 08:00 AM EDT Reads: 2,408
An IoT product’s log files speak volumes about what’s happening with your products in the field, pinpointing current and potential issues, and enabling you to predict failures and save millions of dollars in inventory. But until recently, no one knew how to listen. In his session at @ThingsExpo, Dan Gettens, Chief Research Officer at OnProcess, will discuss recent research by Massachusetts Institute of Technology and OnProcess Technology, where MIT created a new, breakthrough analytics model f...
Sep. 28, 2016 08:00 AM EDT Reads: 2,049
There are several IoTs: the Industrial Internet, Consumer Wearables, Wearables and Healthcare, Supply Chains, and the movement toward Smart Grids, Cities, Regions, and Nations. There are competing communications standards every step of the way, a bewildering array of sensors and devices, and an entire world of competing data analytics platforms. To some this appears to be chaos. In this power panel at @ThingsExpo, moderated by Conference Chair Roger Strukhoff, Bradley Holt, Developer Advocate a...
Sep. 28, 2016 07:45 AM EDT Reads: 2,243
Fifty billion connected devices and still no winning protocols standards. HTTP, WebSockets, MQTT, and CoAP seem to be leading in the IoT protocol race at the moment but many more protocols are getting introduced on a regular basis. Each protocol has its pros and cons depending on the nature of the communications. Does there really need to be only one protocol to rule them all? Of course not. In his session at @ThingsExpo, Chris Matthieu, co-founder and CTO of Octoblu, walk you through how Oct...
Sep. 28, 2016 07:45 AM EDT Reads: 2,256
As organizations shift towards IT-as-a-service models, the need for managing and protecting data residing across physical, virtual, and now cloud environments grows with it. Commvault can ensure protection, access and E-Discovery of your data – whether in a private cloud, a Service Provider delivered public cloud, or a hybrid cloud environment – across the heterogeneous enterprise. In his general session at 18th Cloud Expo, Randy De Meno, Chief Technologist - Windows Products and Microsoft Part...
Sep. 28, 2016 07:30 AM EDT Reads: 2,873
SYS-CON Events announced today that Bsquare has been named “Silver Sponsor” of SYS-CON's @ThingsExpo, which will take place on November 1–3, 2016, at the Santa Clara Convention Center in Santa Clara, CA. For more than two decades, Bsquare has helped its customers extract business value from a broad array of physical assets by making them intelligent, connecting them, and using the data they generate to optimize business processes.
Sep. 28, 2016 07:30 AM EDT Reads: 2,902
There is little doubt that Big Data solutions will have an increasing role in the Enterprise IT mainstream over time. Big Data at Cloud Expo - to be held November 1-3, 2016, at the Santa Clara Convention Center in Santa Clara, CA - has announced its Call for Papers is open. Cloud computing is being adopted in one form or another by 94% of enterprises today. Tens of billions of new devices are being connected to The Internet of Things. And Big Data is driving this bus. An exponential increase is...
Sep. 28, 2016 07:00 AM EDT Reads: 2,685
IoT offers a value of almost $4 trillion to the manufacturing industry through platforms that can improve margins, optimize operations & drive high performance work teams. By using IoT technologies as a foundation, manufacturing customers are integrating worker safety with manufacturing systems, driving deep collaboration and utilizing analytics to exponentially increased per-unit margins. However, as Benoit Lheureux, the VP for Research at Gartner points out, “IoT project implementers often ...
Sep. 28, 2016 07:00 AM EDT Reads: 3,459
SYS-CON Events announced today that Tintri Inc., a leading producer of VM-aware storage (VAS) for virtualization and cloud environments, will exhibit at the 19th International Cloud Expo, which will take place on November 1–3, 2016, at the Santa Clara Convention Center in Santa Clara, CA. Tintri VM-aware storage is the simplest for virtualized applications and cloud. Organizations including GE, Toyota, United Healthcare, NASA and 6 of the Fortune 15 have said “No to LUNs.” With Tintri they mana...
Sep. 28, 2016 07:00 AM EDT Reads: 2,879
The Internet of Things will challenge the status quo of how IT and development organizations operate. Or will it? Certainly the fog layer of IoT requires special insights about data ontology, security and transactional integrity. But the developmental challenges are the same: People, Process and Platform and how we integrate our thinking to solve complicated problems. In his session at 19th Cloud Expo, Craig Sproule, CEO of Metavine, will demonstrate how to move beyond today's coding paradigm ...
Sep. 28, 2016 07:00 AM EDT Reads: 3,359
So, you bought into the current machine learning craze and went on to collect millions/billions of records from this promising new data source. Now, what do you do with them? Too often, the abundance of data quickly turns into an abundance of problems. How do you extract that "magic essence" from your data without falling into the common pitfalls? In her session at @ThingsExpo, Natalia Ponomareva, Software Engineer at Google, provided tips on how to be successful in large scale machine learning...
Sep. 28, 2016 07:00 AM EDT Reads: 2,086
Digitization is driving a fundamental change in society that is transforming the way businesses work with their customers, their supply chains and their people. Digital transformation leverages DevOps best practices, such as Agile Parallel Development, Continuous Delivery and Agile Operations to capitalize on opportunities and create competitive differentiation in the application economy. However, information security has been notably absent from the DevOps movement. Speed doesn’t have to negat...
Sep. 28, 2016 07:00 AM EDT Reads: 2,239