Intel Cloud summit: Big Data by Nick KnupfferPresentation Transcript
Big Data Nick Knupffer Marketing Director PRC & APAC DCSG, Intel1
Video goes hereVideo download link:https://dl.dropbox.com/u/85091041/INTEL_BIG_DATAv20_HD.mov
Every two days, we create as much information as we did from the dawn of civilization up until 200333
Big Data Phenomenon 1.8ZB in 2011 750 Million 966PB 2 Days > the dawn of civilization Photos uploaded to Facebook in Stored in US manufacturing to 2003 2 days (2009) 209 Billion 200+TB 200PB RFID tags sale in 2021: A boy’s 240’000 hours by a MIT Storage of a Smart City project from 12 million in 2011 Media Lab geek in China $800B $300B /year $32+B in personal location data within US healthcare saving from Big Acquisitions by 4 big players 10 years Data since 2010 “Data are becoming the new raw material of business: an economic input almost on a par with capital and labor.” —The Economist, 2010 “Information will be the ‘oil of the 21st century.’” —Gartner, 201044
What is Big Data? Traditional Data Big Data Volume Gigabytes to Terabytes Petabytes and beyond Velocity Occasional Batch – Real-Time Data Analytics Complex Event Processing Variety Centralized, Structured Distributed, i.e. Database Unstructured Multi-format Vast Amounts of Information; Virtually Free55
The Challenges of Big Data Massive scale and growth of unstructured data 80%~90% of total data Volume Growing 10x~50x faster than structured (relational) data 10x~100x of traditional data warehousing Realtime rather than batch-style analysis Velocity Data streamed in, tortured, and discarded Making impact on the spot rather than after-the-fact Heterogeneity and variable nature of Big Data Many different forms (text, document, image, video, ...) Variety No schema or weak schema Inconsistent syntax and semantics66
Why is Big Data Important? Smart City Project: Up to 50% Decrease Improve Public in Product Safety, Boost Development and Economic Growth Assembly Costs1 Online Retailer Generate Revenue Generated 30% of from Data Analytics Sales Due to of B2B Sales? Analytics Driven Recomendations1 Data is the Raw Material of the Information Age1::McKinsey Global Institute Analysis77 *Other brands and names are the property of their respective owners.
Big Data Solutions: VolumeTraditional Storage Distributed Storage Architecture Application Servers Application Ten 9’s Durability & Storage Client 50% Lower TCO Metadata Storage Servers Servers SAN Metadata Storage (Storage Area Services Services Network) 1000s of Nodes & >200GB’s/sec Performance88 *Other brands and names are the property of their respective owners.
Big Data Solutions: Velocity In Memory Analytics Network Edge Analytics Stream Processing Analysis & Decision Support Applications Search and Analysis of 53 Million Customer Analyze Data as its Collected to Records: Make Near Real-time Decisions From 2-3 Hours to 2-3 Seconds!1991: Hilti Corporation case study *Other brands and names are the property of their respective owners.
Big Data Solutions: Variety Unstructured Emerging Analytical Paradigms Multi-format Data Technologies Structured Data Relational Database EXALYTICS1010 *Other brands and names are the property of their respective owners.
Big Data is Different from Traditional Data New Workloads/Methodologies to Design New Platforms Processing Data Management Analytics Real-time Analytics Distributed Analytics Scale-up Distributed Processing Speed Platform Hierarchy Descriptive Analytics Predictive/Prescriptive Analytics Relational Database NoSQL and NewSQL (SQL) Data Warehouse Flexible Scale-Out Schema Cluster Platform Batch-style Analytics Volume 1x 10x 100x Traditional Data Big Data1111
The Major Source of Sensed Data Internet of Things (IoT) and Smart City Internet of Things (IoT) is a major source Most IoT apps are relevant for sensed data to Smart City, funded by governments Intelligence Environment Protection (Processing) Smart Agriculture Smart Logistics Interconnect Public Safety (Communication) E-Health Intelligence Intelligent Transportation (Control) Smart Home Smart Grid Instrumentation Industrial Automation (Sensing)1212 Source: GreatWall Strategy Consultants
Intel’s Role in BigData1313
Intel’s Role in Big Data Accelerating big data analytics through faster and more effective CPU, Storage, I/O, Network platform. Driving innovation in big data applications by providing optimized software stack and services. Foster the growth of big data ecosystem through broad collaboration with partners. Investing in Solution Research and Services for Big DataData of any type, under any provisioning method, is analyzed to find insights that drive business, social, and ecological value.1414
Universal Insights Instant analysis at every level, from the sensor to the datacenter Visualization & Interpretation [Un]Structured Horizontal & Vertical Scale Streaming Batch E7 Analytics Analytics Data E5 Data Acquisition Microserver E3 Local Analytics Complex Event Processing Analytics Processing Preprocessing/ Storage Cleansing/Filtering/ Aggregation Horizontal Scale Data Acquisition Video Analytics Sensors Cameras Every device that consumes electricity, should compute.1515 Every device that computes, should also analyze.
Example: Intel AIM View - Face Detection Two viewers detected Demographics analyzed: Gender: Males Age bracket: Adults Show targeted content Viewing Information Collected: Person 1: 10 seconds , Person 2: 8 seconds Built-In Privacy Protection - No images are recorded and no personal information is collected Accuracy Levels: Face detection: ~98% Gender: ~86% Age: ~70% to 80% depending on life stage bracket (child, young adult, adult, senior citizen) Distance: Up to 15 ft. or 35ft. depending on camera resolution Other names and brands may be claimed as the property of other respected companies1616
Immediate Insights Intel builds performance customized and optimized extreme solutions to drive immediate insights and discoveries. From Telecoms, to Financial Services, to Smart cities, Manufacturing and Healthcare, Intel delivers robust security and trusted extreme performance computing, software, storage and network solutions customized and optimized for every industry; leading to insights and discoveries that better our1717 world.
Insights for everyone New analytics economics through scale and standards. Smart Building Smart Grid sensors sensors Industrial Automation Pollution sensors sensors Meteorological Smart sensors meters INTELLIGENT CITY INTELLIGENT FACTORY INTELLIGENT INTELLIGENT HOSPITAL HIGHWAY Sensors on Inductive Traffic cameras Portable medical Medical sensors Smartphone Sensors on sensors imaging services on ambulances Vehicles Intel’s open platforms, open software, open standards approach and industry leadership will drive down the cost and drive up the pace of innovation, putting affordable Big Data analytical capabilities within everyone’s reach.1818
Summary 1 Big Data is here and growing rapidly 2 Intel is well positioned from a software stack and platform basis 3 Intel is committed to investing in new technology to address more demanding big data requirements of the future1919
Risk Factors The above statements and any others in this document that refer to plans and expectations for the first quarter, the year and the future are forward-looking statements that involve a number of risks and uncertainties. Words such as “anticipates,” “expects,” “intends,” “plans,” “believes,” “seeks,” “estimates,” “may,” “will,” “should” and their variations identify forward-looking statements. Statements that refer to or are based on projections, uncertain events or assumptions also identify forward-looking statements. Many factors could affect Intel’s actual results, and variances from Intel’s current expectations regarding such factors could cause actual results to differ materially from those expressed in these forward-looking statements. Intel presently considers the following to be the important factors that could cause actual results to differ materially from the company’s expectations. Demand could be different from Intels expectations due to factors including changes in business and economic conditions, including supply constraints and other disruptions affecting customers; customer acceptance of Intel’s and competitors’ products; changes in customer order patterns including order cancellations; and changes in the level of inventory at customers. Uncertainty in global economic and financial conditions poses a risk that consumers and businesses may defer purchases in response to negative financial events, which could negatively affect product demand and other related matters. Intel operates in intensely competitive industries that are characterized by a high percentage of costs that are fixed or difficult to reduce in the short term and product demand that is highly variable and difficult to forecast. Revenue and the gross margin percentage are affected by the timing of Intel product introductions and the demand for and market acceptance of Intels products; actions taken by Intels competitors, including product offerings and introductions, marketing programs and pricing pressures and Intel’s response to such actions; and Intel’s ability to respond quickly to technological developments and to incorporate new features into its products. Intel is in the process of transitioning to its next generation of products on 22nm process technology, and there could be execution and timing issues associated with these changes, including products defects and errata and lower than anticipated manufacturing yields. The gross margin percentage could vary significantly from expectations based on capacity utilization; variations in inventory valuation, including variations related to the timing of qualifying products for sale; changes in revenue levels; product mix and pricing; the timing and execution of the manufacturing ramp and associated costs; start-up costs; excess or obsolete inventory; changes in unit costs; defects or disruptions in the supply of materials or resources; product manufacturing quality/yields; and impairments of long-lived assets, including manufacturing, assembly/test and intangible assets. The majority of Intel’s non-marketable equity investment portfolio balance is concentrated in companies in the flash memory market segment, and declines in this market segment or changes in management’s plans with respect to Intel’s investments in this market segment could result in significant impairment charges, impacting restructuring charges as well as gains/losses on equity investments and interest and other. Intels results could be affected by adverse economic, social, political and physical/infrastructure conditions in countries where Intel, its customers or its suppliers operate, including military conflict and other security risks, natural disasters, infrastructure disruptions, health concerns and fluctuations in currency exchange rates. Expenses, particularly certain marketing and compensation expenses, as well as restructuring and asset impairment charges, vary depending on the level of demand for Intels products and the level of revenue and profits. Intel’s results could be affected by the timing of closing of acquisitions and divestitures. Intels results could be affected by adverse effects associated with product defects and errata (deviations from published specifications), and by litigation or regulatory matters involving intellectual property, stockholder, consumer, antitrust and other issues, such as the litigation and regulatory matters described in Intels SEC reports. An unfavorable ruling could include monetary damages or an injunction prohibiting us from manufacturing or selling one or more products, precluding particular business practices, impacting Intel’s ability to design its products, or requiring other remedies such as compulsory licensing of intellectual property. A detailed discussion of these and other factors that could affect Intel’s results is included in Intel’s SEC filings, including the report on Form 10-Q for the quarter ended Oct. 1, 2011. Rev. 1/19/122222