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Difference Between #BigData and Internet of Things | @ThingsExpo #IoT #M2M
What does it mean, as a vendor, to say that you support the Internet of Things (IoT) from an analytics perspective?

A recent argument with folks whose intelligence I hold in high regard (like Tom, Brandon, Wei, Anil, etc.) got me thinking about the following question:

What does it mean, as a vendor, to say that you support the Internet of Things (IoT) from an analytics perspective?

I think the heart of that question really boils down to this:

What are the differences between big data (which is analyzing large amounts of mostly human-generated data to support longer-duration use cases such as predictive maintenance, capacity planning, customer 360 and revenue protection) and IoT (which is aggregating and compressing massive amounts of low latency / low duration / high volume machine-generated data coming from a wide variety of sensors to support real-time use cases such as operational optimization, real-time ad bidding, fraud detection, and security breach detection)?

I don’t believe that loading sensor data into a data lake and performing data science to create predictive analytic models qualifies as doing IoT analytics.  To me, that’s just big data (and potentially REALLY BIG DATA with all that sensor data).  In order for one to claim that they can deliver IoT analytic solutions requires big data (with data science and a data lake), but IoT analytics must also include:

  1. Streaming data management with the ability to ingest, aggregate (e.g., mean, median, mode) and compress real-time data coming off a wide variety of sensor devices “at the edge” of the network, and
  2. Edge analytics that automatically analyzes real-time sensor data and renders real-time decisions (actions) at the edge of the network that optimizes operational performance (blade angle or yaw) or flags unusual performance or behaviors for immediate investigation (security breaches, fraud detection).

If you cannot manage real-time streaming data and make real-time analytics and real-time decisions at the edge, then you are not doing IOT or IOT analytics, in my humble opinion.  So what is required to support these IoT data management and analytic requirements?

The IoT “Analytics” Challenge
The Internet of Things (or Industrial Internet) operates at machine-scale, by dealing with machine-to-machine generated data.  This machine-generated data creates discrete observations (e.g., temperature, vibration, pressure, humidity) at very high signal rates (1,000s of messages/sec).  Add to this the complexity that the sensor data values rarely change (e.g., temperature operates within an acceptably small range).  However, when the values do change the ramifications, the changes will likely be important.

Consequently to support real-time edge analytics, we need to provide detailed data that can flag observations of concern, but then doesn’t overwhelm the ability to get meaningful data back to the core (data lake) for more broad-based, strategic analysis.

One way that we see organizations addressing the IoT analytics needs is via a 3-tier Analytics Architecture (see Figure 1).

Figure 1: IoT Analytics 3-Tier Architecture

We will use a wind turbine farm to help illustrate the 3-tier analytics architecture capabilities.

Tier 1 performs individual wind turbine real-time performance analysis and optimization.  Tier 1 must manage (ingest and compress) real-time data streams coming off of multiple, heterogeneous sensors. Tier 1 analyzes the data, and processes the incoming data against static or dynamically updated analytic models (e.g., rules-based, decision trees) for immediate or near-immediate actions.

Purpose-built T1 edge gateways leverage real-time data compression techniques (e.g., see the article “timeseries storage and data compression” for more information on timeseries databases) to only send a subset of the critical data (e.g., data that has changed) back to T2 and T3 (core).

Let’s say that you are monitoring the temperatures of a compressor inside of a large industrial engine.  Let’s say the average temperature of that compressor is 99 degrees, and only varies between 98 to 100 degrees within a 99% confidence level.  Let’s also say the compressor is emitting the following temperature readings 10 times a second:

99, 99, 99, 98, 98, 99, 99, 98, 99, 99, 100, 99, 99, 99, 100, 99, 98, 99, 99…

You have 10,000 of readings that don’t vary from that range.  So why send all of the readings (which from a transmission bandwidth perspective could be significant)?  Instead, use a timeseries database to only send mean, medium, mode, variances, standard deviation and other statistical variables of the 10,000 readings instead of the individual 10,000 readings.

However, let’s say that all of a sudden we start getting readings outside the normal 99% confidence level:

99, 99, 99, 100, 100, 101, 101, 102, 102, 103, 104, 104, 105, …

Then we’d apply basic Change Data Capture (CDC) techniques to capture and transmit the subset of critical data to T2 and T3 (core).

Consequently, edge gateways leverage timeseries compression techniques to drive faster automated decisions while only sending a subset of critical data to the core for further analysis and action.

The Tier 1 analytics are likely being done via an on-premise analytics server or gateway (see Figure 2).

Figure 2:  IoT Tier 1 Analytics

Tier 2 optimizes performance and predicts maintenance needs across the wind turbines in the same wind farm.  Tier 2 requires a distributed dynamic content processing rule generation and execution analytics engine that integrates and analyzes data aggregated across the potentially heterogeneous wind turbines. Cohort analysis is typical in order to identify, validate and codify performance problems and opportunities across the cohort wind turbines.  For example, in the wind farm, the Tier 2 analytics are responsible for real-time learning that can generate the optimal torque and position controls for the individual wind turbines. Tier 2 identifies and shares best practices across the wind turbines in the wind farm without having to be dependent upon the Tier 3 core analytics platform (see Figure 3).

Figure 3: Tier 2 Analytics: Optimizing Cohort Performance

Tier 3 is the data lake enabled core analytics platform. The tier 3 core analytics platform includes analytics engines, data sets and data management services (e.g., governance, metadata management, security, authentication) that enable access to the data (sensor data plus other internal and external data sources) and existing analytic models that supports data science analytic/predictive model development and refinement.  Tier 3 aggregates the critical data across all wind farms and individual turbines, and combines the sensor data with external data sources which could include weather (humidity, temperatures, precipitation, air particles, etc.), electricity prices, wind turbine maintenance history, quality scores for the wind turbine manufacturers, and performance profiles of the wind turbine mechanics and technicians (see Figure 4).

Figure 4:  Core Analytics for Analytic Model Development and Refinement

With the rapid increase in storage and processing power at the edges of the Internet of Things (for example, the Dell Edge Gateway 3000 Series), we will see more and more analytic capabilities being pushed to the edge.

How Do You Start Your IoT Journey
While the rapidly evolving expertise on the IoT edge technologies can be very exciting (graphical processing units in gateway servers with embedded machine learning capabilities with 100’s of gigabytes of storage), the starting point for the IoT journey must first address this basic question:

How effective is your organization at leveraging data and analytics to power your business (or operational) models?

We have tweaked the Big Data Business Model Maturity Index to help organizations not only understand where they sit on the maturity index with respect to the above question, but also to provide a roadmap for how organizations can advance up the maturity index to become more effective at leveraging the wealth of IOT data with advanced analytics to power their business and operational models (see Figure 5).

Figure 5:  Big Data / IoT Business Model Maturity IndexMaturity Index

To drive meaningful business impact, you will need to begin with the business and not the technology:

  • Engage the business stakeholders on day one,
  • Align the business and IT teams
  • Understand the organization’s key business and operational initiatives, and
  • Identify and prioritize the use cases (decisions/goals) that support those business initiatives.

If you want to monetize your IOT initiatives, follow those simple guidelines and you will dramatically increase the probability of your business and monetization success.

For more details on the Internet of Things revolution, check out these blogs:

The post Difference between Big Data and Internet of Things appeared first on InFocus Blog | Dell EMC Services.

About William Schmarzo
Bill Schmarzo, author of “Big Data: Understanding How Data Powers Big Business”, is responsible for setting the strategy and defining the Big Data service line offerings and capabilities for the EMC Global Services organization. As part of Bill’s CTO charter, he is responsible for working with organizations to help them identify where and how to start their big data journeys. He’s written several white papers, avid blogger and is a frequent speaker on the use of Big Data and advanced analytics to power organization’s key business initiatives. He also teaches the “Big Data MBA” at the University of San Francisco School of Management.

Bill has nearly three decades of experience in data warehousing, BI and analytics. Bill authored EMC’s Vision Workshop methodology that links an organization’s strategic business initiatives with their supporting data and analytic requirements, and co-authored with Ralph Kimball a series of articles on analytic applications. Bill has served on The Data Warehouse Institute’s faculty as the head of the analytic applications curriculum.

Previously, Bill was the Vice President of Advertiser Analytics at Yahoo and the Vice President of Analytic Applications at Business Objects.

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Cloud Expo 2013 East Opening Keynote by IBM
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Top Stories for Cloud Expo 2012 East

In this Big Data Power Panel at the 10th International Cloud Expo, moderated by Cloud Expo Conference Chair Jeremy Geelan, Govind Rangasamy, Director of Product Management at Eucalyptus Systems; Kevin Brown; CEO of Coraid, Inc.; Christos Tryfonas, CTO and Co-Founder of Cetas; and Max Riggsbee, CMO and VP of Products for WhipTail, discussed such topics as: Big Data has existed since the early days of computing; why, then, do you think there is such an industry buzz around it right now? How is Big Data impacting storage and networking architecture in data centers? How about the intersection of Big Data Analytics and Cloud Computing - how big a sector is that and why? What's the difference between Big Data and Fast Data? ... (more)

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There is little doubt that Big Data solutions will have an increasing role in the Enterprise IT mainstream over time. Get a jump on that rapidly evolving trend at Big Data Expo, which we are introducing in June at
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AHMAR ABBAS
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With our launch at Cloud Expo, we successfully transformed the company from a relatively unknown European player into the dominant player in the market. Our competitors were taken by surprise and just blown away. We got a huge number of really high quality leads..."
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@CloudExpo Blogs
In this strange new world where more and more power is drawn from business technology, companies are effectively straddling two paths on the road to innovation and transformation into digital enterprises. The first path is the heritage trail – with “legacy” technology forming the background. Here, extant technologies are transformed by core IT teams to provide more API-driven approaches. Legacy systems can restrict companies that are transitioning into digital enterprises. To truly become a leader in the space, it’s necessary to accommodate, incorporate, and exploit the new breed of enterprise...
When it comes to cloud computing, the ability to turn massive amounts of compute cores on and off on demand sounds attractive to IT staff, who need to manage peaks and valleys in user activity. With cloud bursting, the majority of the data can stay on premises while tapping into compute from public cloud providers, reducing risk and minimizing need to move large files. In his session at 18th Cloud Expo, Scott Jeschonek, Director of Product Management at Avere Systems, discussed the IT and business benefits that cloud bursting provides, including increased compute capacity, lower IT investment,...
Digital transformation leaders have poured tons of money and effort into coding in recent years. And with good reason. To succeed at digital, you must be able to write great code. You also have to build a strong Agile culture so your coding efforts tightly align with market signals and business outcomes. But if your investments in testing haven’t kept pace with your investments in coding, you’ll lose. But if your investments in testing haven’t kept pace with your investments in coding, you’ll lose. Here’s why: Reason #1: Functional testing is one of your worst DevOps bottlenecks.
SYS-CON Events announced today that IBM has been named “Diamond Sponsor” of SYS-CON's 21st Cloud Expo, which will take place on October 31 through November 2nd 2017 at the Santa Clara Convention Center in Santa Clara, California.
Infoblox delivers Actionable Network Intelligence to enterprise, government, and service provider customers around the world. They are the industry leader in DNS, DHCP, and IP address management, the category known as DDI. We empower thousands of organizations to control and secure their networks from the core-enabling them to increase efficiency and visibility, improve customer service, and meet compliance requirements.
Join IBM November 1 at 21st Cloud Expo at the Santa Clara Convention Center in Santa Clara, CA, and learn how IBM Watson can bring cognitive services and AI to intelligent, unmanned systems. Cognitive analysis impacts today’s systems with unparalleled ability that were previously available only to manned, back-end operations. Thanks to cloud processing, IBM Watson can bring cognitive services and AI to intelligent, unmanned systems. Imagine a robot vacuum that becomes your personal assistant that knows everything and can respond to your emotions and verbal commands!
In a recent survey, Sumo Logic surveyed 1,500 customers who employ cloud services such as Amazon Web Services (AWS), Microsoft Azure, and Google Cloud Platform (GCP). According to the survey, a quarter of the respondents have already deployed Docker containers and nearly as many (23 percent) are employing the AWS Lambda serverless computing framework. It’s clear: serverless is here to stay. The adoption does come with some needed changes, within both application development and operations. That means serverless is also changing the way we leverage public clouds. Truth-be-told, many enterpris...
SYS-CON Events announced today that Avere Systems, a leading provider of enterprise storage for the hybrid cloud, will exhibit at SYS-CON's 21st International Cloud Expo®, which will take place on Oct 31 - Nov 2, 2017, at the Santa Clara Convention Center in Santa Clara, CA. Avere delivers a more modern architectural approach to storage that doesn't require the overprovisioning of storage capacity to achieve performance, overspending on expensive storage media for inactive data or the overbuilding of data centers to house increasing amounts of storage infrastructure.
With major technology companies and startups seriously embracing Cloud strategies, now is the perfect time to attend 21st Cloud Expo October 31 - November 2, 2017, at the Santa Clara Convention Center, CA, and June 12-14, 2018, at the Javits Center in New York City, NY, and learn what is going on, contribute to the discussions, and ensure that your enterprise is on the right path to Digital Transformation.
Digital transformation is changing the face of business. The IDC predicts that enterprises will commit to a massive new scale of digital transformation, to stake out leadership positions in the "digital transformation economy." Accordingly, attendees at the upcoming Cloud Expo | @ThingsExpo at the Santa Clara Convention Center in Santa Clara, CA, Oct 31-Nov 2, will find fresh new content in a new track called Enterprise Cloud & Digital Transformation.
Most technology leaders, contemporary and from the hardware era, are reshaping their businesses to do software. They hope to capture value from emerging technologies such as IoT, SDN, and AI. Ultimately, irrespective of the vertical, it is about deriving value from independent software applications participating in an ecosystem as one comprehensive solution. In his session at @ThingsExpo, Kausik Sridhar, founder and CTO of Pulzze Systems, will discuss how given the magnitude of today's application ecosystem, tweaking existing software to stitch various components together leads to sub-optimal ...
Join IBM November 1 at 21st Cloud Expo at the Santa Clara Convention Center in Santa Clara, CA, and learn how IBM Watson can bring cognitive services and AI to intelligent, unmanned systems. Cognitive analysis impacts today’s systems with unparalleled ability that were previously available only to manned, back-end operations. Thanks to cloud processing, IBM Watson can bring cognitive services and AI to intelligent, unmanned systems. Imagine a robot vacuum that becomes your personal assistant that knows everything and can respond to your emotions and verbal commands!
Enterprises are adopting Kubernetes to accelerate the development and the delivery of cloud-native applications. However, sharing a Kubernetes cluster between members of the same team can be challenging. And, sharing clusters across multiple teams is even harder. Kubernetes offers several constructs to help implement segmentation and isolation. However, these primitives can be complex to understand and apply. As a result, it’s becoming common for enterprises to end up with several clusters. This leads to a waste of cloud resources and increased operational overhead.
Today most companies are adopting or evaluating container technology - Docker in particular - to speed up application deployment, drive down cost, ease management and make application delivery more flexible overall. As with most new architectures, this dream takes significant work to become a reality. Even when you do get your application componentized enough and packaged properly, there are still challenges for DevOps teams to making the shift to continuous delivery and achieving that reduction in cost and increase in speed. Sometimes in order to reduce complexity teams compromise features ...
With major technology companies and startups seriously embracing Cloud strategies, now is the perfect time to attend 21st Cloud Expo October 31 - November 2, 2017, at the Santa Clara Convention Center, CA, and June 12-14, 2018, at the Javits Center in New York City, NY, and learn what is going on, contribute to the discussions, and ensure that your enterprise is on the right path to Digital Transformation.
Organizations do not need a Big Data strategy; they need a business strategy that incorporates Big Data. Most organizations lack a road map for using Big Data to optimize key business processes, deliver a differentiated customer experience, or uncover new business opportunities. They do not understand what’s possible with respect to integrating Big Data into the business model.
SYS-CON Events announced today that IBM has been named “Diamond Sponsor” of SYS-CON's 21st Cloud Expo, which will take place on October 31 through November 2nd 2017 at the Santa Clara Convention Center in Santa Clara, California.
"We provide IoT solutions. We provide the most compatible solutions for many applications. Our solutions are industry agnostic and also protocol agnostic," explained Richard Han, Head of Sales and Marketing and Engineering at Systena America, in this SYS-CON.tv interview at @ThingsExpo, held June 6-8, 2017, at the Javits Center in New York City, NY.
Shiny new toy syndrome. We all see it, we all experience it. Who doesn’t like the shiny new toy? Whenever a new technology hits the high points of hype, everyone starts talking about it like it will solve all their business problems. Sadly, frequently without even looking at what problem they are trying to solve. Blockchain is one of those technologies. According to Gartner’s latest report on the hype cycle of emerging technologies, blockchain has just passed the peak of their hype cycle curve. If you read the news articles about it, one would think it has taken over the technology world. The...
Machine Learning needs tons of data. But what are you going to do when the data only exist in the heads of your employees? Machine Learning, Deep Learning, Cognitive Computing, Robotic Process Automation (RPA), Natural Language Processing (NLP), Machine Perception, Predictive APIs, Image Recognition, Speech Recognition, Virtual Agent, Intelligent Assistant, Personal Advisor, Chatbot, Semantic Search. Did I miss anything? I am sure I did. However, I guess I provide a good list for your next round of Artificial Intelligence (AI) bullshit bingo. Oh, one last thing - Machine Reasoning! If you've ...
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Past SYS-CON Events
    Cloud Expo West
cloudcomputingexpo
2011west.sys-con.com

 
    Cloud Expo East
cloudcexpo
2011east.sys-con.com

 
    Cloud Expo West
cloudcomputingexpo
2010west.sys-con.com

 
    Virtualization Expo West
virtualization
2010west.sys-con.com
    Cloud Expo Europe
cloudexpoeurope2010.
sys-con.com

 
    Cloud Expo East
cloudcomputingexpo
2010east.sys-con.com

 
    Virtualization Expo East
virtualizationconference
2010east.sys-con.com
    Cloud Expo West
cloudcomputingexpo
2009west.sys-con.com

 
    Virtualization Expo West
virtualizationconference
2009west.sys-con.com
    GovIT Expo
govitexpo.com
 
    Cloud Expo Europe
cloudexpoeurope2009.sys-con.com
 

Cloud Expo 2011 Allstar Conference Faculty

S.F.S.
Dell

Singer
NRO

Pereyra
Oracle

Ryan
OpSource

Butte
PwC

Leone
Oracle

Riley
AWS

Varia
AWS

Lye
Oracle

O'Connor
AppZero

Crandell
RightScale

Nucci
Dell Boomi

Hillier
CiRBA

Morrison
Layer 7 Tech

Robbins
NYT

Schwarz
Oracle

What The Enterprise IT World Says About Cloud Expo
 
"We had extremely positive feedback from both customers and prospects that attended the show and saw live demos of NaviSite's enterprise cloud based services."
  –William Toll
Sr. Director, Marketing & Strategic Alliances
Navisite
 


 
"More and better leads than ever expected! I have 4-6 follow ups personally."
  –Richard Wellner
Chief Scientist
Univa UD
 


 
"Good crowd, good questions. The event looked very successful."
  –Simon Crosby
CTO
Citrix Systems
 


 
"It's the largest cloud computing conference I've ever seen."
  –David Linthicum
CTO
Brick Group