Welcome!

@CloudExpo Authors: Elizabeth White, Liz McMillan, Yeshim Deniz, Pat Romanski, Aruna Ravichandran

Related Topics: @ThingsExpo, @CloudExpo, @BigDataExpo

@ThingsExpo: Article

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.

More Stories By 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.

@CloudExpo Stories
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.
Enterprises have taken advantage of IoT to achieve important revenue and cost advantages. What is less apparent is how incumbent enterprises operating at scale have, following success with IoT, built analytic, operations management and software development capabilities – ranging from autonomous vehicles to manageable robotics installations. They have embraced these capabilities as if they were Silicon Valley startups. As a result, many firms employ new business models that place enormous impor...
Amazon is pursuing new markets and disrupting industries at an incredible pace. Almost every industry seems to be in its crosshairs. Companies and industries that once thought they were safe are now worried about being “Amazoned.”. The new watch word should be “Be afraid. Be very afraid.” In his session 21st Cloud Expo, Chris Kocher, a co-founder of Grey Heron, will address questions such as: What new areas is Amazon disrupting? How are they doing this? Where are they likely to go? What are th...
SYS-CON Events announced today that MIRAI Inc. will exhibit at the Japan External Trade Organization (JETRO) Pavilion 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. MIRAI Inc. are IT consultants from the public sector whose mission is to solve social issues by technology and innovation and to create a meaningful future for people.
SYS-CON Events announced today that Dasher Technologies 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. Dasher Technologies, Inc. ® is a premier IT solution provider that delivers expert technical resources along with trusted account executives to architect and deliver complete IT solutions and services to help our clients execute their goals, plans and objectives. Since 1999, we'v...
Though cloud is the future of enterprise computing, a smooth transition of legacy applications and systems is critical for seamless business operations. IT professionals are eager to start leveraging the cost, scale and other benefits of cloud, but with massive investments already in place in existing infrastructure and a number of compliance and resource hurdles, it can be challenging to move to a cloud-based infrastructure.
SYS-CON Events announced today that NetApp has been named “Bronze Sponsor” of 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. NetApp is the data authority for hybrid cloud. NetApp provides a full range of hybrid cloud data services that simplify management of applications and data across cloud and on-premises environments to accelerate digital transformation. Together with their partners, NetApp emp...
In his session at 21st Cloud Expo, Raju Shreewastava, founder of Big Data Trunk, will provide a fun and simple way to introduce Machine Leaning to anyone and everyone. Together we will solve a machine learning problem and find an easy way to be able to do machine learning without even coding. Raju Shreewastava is the founder of Big Data Trunk (www.BigDataTrunk.com), a Big Data Training and consulting firm with offices in the United States. He previously led the data warehouse/business intellige...
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.
SYS-CON Events announced today that TidalScale, a leading provider of systems and services, 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. TidalScale has been involved in shaping the computing landscape. They've designed, developed and deployed some of the most important and successful systems and services in the history of the computing industry - internet, Ethernet, operating s...
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.
In his session at 21st Cloud Expo, Michael Burley, a Senior Business Development Executive in IT Services at NetApp, will describe how NetApp designed a three-year program of work to migrate 25PB of a major telco's enterprise data to a new STaaS platform, and then secured a long-term contract to manage and operate the platform. This significant program blended the best of NetApp’s solutions and services capabilities to enable this telco’s successful adoption of private cloud storage and launchi...
Data scientists must access high-performance computing resources across a wide-area network. To achieve cloud-based HPC visualization, researchers must transfer datasets and visualization results efficiently. HPC clusters now compute GPU-accelerated visualization in the cloud cluster. To efficiently display results remotely, a high-performance, low-latency protocol transfers the display from the cluster to a remote desktop. Further, tools to easily mount remote datasets and efficiently transfer...
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.
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 tha...
In his Opening Keynote at 21st Cloud Expo, John Considine, General Manager of IBM Cloud Infrastructure, will lead you through the exciting evolution of the cloud. He'll look at this major disruption from the perspective of technology, business models, and what this means for enterprises of all sizes. John Considine is General Manager of Cloud Infrastructure Services at IBM. In that role he is responsible for leading IBM’s public cloud infrastructure including strategy, development, and offering ...
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. Tha...
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 overbui...
In his general session at 21st Cloud Expo, Greg Dumas, Calligo’s Vice President and G.M. of US operations, will go over the new Global Data Protection Regulation and how Calligo can help business stay compliant in digitally globalized world. Greg Dumas is Calligo's Vice President and G.M. of US operations. Calligo is an established service provider that provides an innovative platform for trusted cloud solutions. Calligo’s customers are typically most concerned about GDPR compliance, applicatio...
Widespread fragmentation is stalling the growth of the IIoT and making it difficult for partners to work together. The number of software platforms, apps, hardware and connectivity standards is creating paralysis among businesses that are afraid of being locked into a solution. EdgeX Foundry is unifying the community around a common IoT edge framework and an ecosystem of interoperable components.