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1 TECHNOLOGY TRENDS FOR 2013 Kaushal Amin, Chief Technology Officer KMS Technology – Atlanta, GA, USA

Technology Trends and Big Data in 2013-2014

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This is the slide deck that KMS Technology's CTO delivered at The 16th Offline of CIO Vietnam Group on Thurdsay, 23/05/2013.

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Page 1: Technology Trends and Big Data in 2013-2014

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TECHNOLOGY TRENDS FOR 2013

Kaushal Amin, Chief Technology OfficerKMS Technology – Atlanta, GA, USA

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ABOUT KMS

Founded in January 2009 with offices in Atlanta, Dublin, Calif., and Ho Chi Minh City, Vietnam, KMS Technology is a US Offshore Product Development (OPD) company.

We have a 400+ global workforce that provides a variety of commercial grade web and software development services to software product and technology-based companies.

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ABOUT SPEAKER – KAUSHAL AMIN

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2011-Now KMS

2006-11 LexisNexis

2001-06 Startups

1999-02 Intel

1993-99 McKesson

1989-93 IBM

1985-88 Engineering

• Bachelors in Computer Engineering from University of Michigan

• Developed OS Cross Assembler in “C” for MC6809

• Developed Windows NT based optical file system for dealing with large data files

• Healthcare Medical Records & Imaging

• Wireless mobile field service software on Windows CE and J2ME

• Developed Price Optimization software for retail and hotel industry

• Provide technical leadership and mentoring to KMS US and Vietnam staff

• Provide “C” level technology consulting to KMS clients

• Part of OS/2 Kernel team

• Atlanta Police Mobile Platform (Motorola)

• Delta Flight Planning & Fueling Systems in Unix

• Intel’s multimedia showcase website in 16 languages and 40+ countries

• One of the early N-tier architected Windows COM+ web system

• Online BIG DATA system of US criminal records, education, and employment history on employees

• LexisNexis ‘s NoSQL distributed database

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WHY SHOULD YOU BE HERE

• Learn about MAJOR software technology trends affecting IT industry and businesses

• Necessary in order to anticipate and respond to ongoing technology-driven disruptions

• Step up. Provoke and harvest disruption. Don’t get caught unaware or unprepared.

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INDUSTRY EXPERTS 2013 LIST

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#1 – MOBILE APPS

• Mobile devices overtaking PCs as the most common web access device worldwide by end of 2013

• More market shift towards complex business applications instead of small niche consumer apps• Similar to PC evolution of desktop productivity

apps to network enabled enterprise solutions

• Apple iOS and Google Android will continue to dominate market share for next 2 years

• Native Apps will continue to be preferred development platform, however, HTML5/Hybrid will start gaining ground

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MOBILE APPS STATS

Mobile App Market Stats:

• The number of smartphones will exceed 1.82 billion units worldwide in 2013 (~ 40% of cell phone market)

• Android is expected to claim 63.8% market share by 2016

• iOS monthly revenues are 4x those of Google Play

• Apple has paid developers $5 billion in app sales

• There are now more than 400 million accounts with registered credit cards in the App Store

• Google Play Has 700,000 Apps, Tying Apple’s App Store

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#2 - BIG DATA

“Big data exceeds the reach of commonly used hardware environments and software tools to capture, manage, and process it with in a tolerable elapsed time for its user population.” - Teradata Magazine article, 2011

“Big data refers to data sets whose size is beyond the ability of typical database software tools to capture, store, manage and analyze.” - The McKinsey Global Institute, 2011

Volume and Variety of Data that is difficult to manage using traditional data management

technology

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WHAT IS GENERATING BIG DATA?

Homeland Security

Real Time Search

Social

eCommerce

User Tracking & Engagement

Financial Services

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HOW MUCH DATA?

• 7 billion people• Google processes 100 PB/day; 3 million servers• Facebook has 300 PB + 500 TB/day; 35% of

world’s photos• YouTube 1000 PB video storage; 4 billion

views/day• Twitter processes124 billion tweets/year• SMS messages – 6.1T per year• US Cell Calls – 2.2T minutes per year• US Credit cards - 1.4B Cards; 20B

transactions/year

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TYPE OF DATA

• Structured Data (Transactions)

• Text Data (Web Content)

• Semi-structured Data (XML)

• Unstructured Data– Social Network, SMS, Audio, Video

• Streaming Data – You can only scan the data once as it travels on network

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RDBMS LIMITATIONS

• Very difficult to scale horizontally (more boxes) as the best way to scale is vertically by utilizing bigger box– Physical limited to CPUs, Disk storage, and memory– Large servers are too expensive and still can’t scale

• Requires structure of tables with rows and columns– Does not deal well with unstructured data

• Relationships have to be pre-defined through schema– Difficult to add newly discovered data quickly

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NOSQL CHARACTERISTICS

• Cheap, easy to implement (open source)– Cluster of cheap commodity servers with cheap storage

• Data are replicated to multiple nodes (therefore identical and fault-tolerant) and can be partitioned– Down nodes can easily be replaced while cluster is operational– No single point of failure

• Easy to distribute• Don't require a schema• Massive Scalability• Relaxed the data consistency requirement

(CAP) – less locking and resource contengency13

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NOSQL – SEVERAL OPTIONS

• Currently 150 implementations and growing (http://nosql-database.org/)

• Multiple Types based on storage architecture– Key-Value– Document– Column Family– Graph

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EXAMPLE: HEALTHCARE BIG DATA

A health care consultancy has made the data coming out of medical practices the focus of its thriving business. The company collects billing and diagnostic code data from 10,000 doctors on a daily, weekly and monthly basis to create a virtual clinical integration model. The consulting company analyzes the data to help the groups understand how well they are meeting the FTC guidelines for negotiating with health plans and whether they qualify for enhanced reimbursement based on offering a more cost-effective standard of care.

It also sends them automated information to better take care of patients, like creating an automated outbound calling system for pediatric patients who weren’t up to date on their vaccinations.

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EXAMPLE: RETAIL BIG DATA

Walmart handles more than 1 million customer transactions every hour, which is imported into databases estimated to contain more than 2.5 petabytes * of data — the equivalent of 167 times the information contained in all the books in the US Library of Congress.

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EXAMPLE: UTILITY BIG DATA

With a smart meter, a utility company goes from collecting one data point a month per customer (using a meter reader in a truck or car) to receiving 3,000 data points for each customer each month, while smart meters send usage information up to four times an hour.

One small Midwestern utility is using smart meter data to structure conservation programs that analyze existing usage to forecast future use, price usage based on demand and share that information with customers who might decide to forestall doing that load of wash until they can pay for it at the nonpeak price.

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#3 - CLOUD COMPUTING

• Shift from “Should we use” to “how can we use cloud” within corporate IT

• Personal Cloud to replace PCs for personal content storage allowing access across multiple devices

• Cloud-based disaster-recovery as-a-service

• De-duplicating and Encryption of data before it is sent to a cloud storage service will be an integral component

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CLOUD COMPUTING

• Start addressing the real drawbacks of cloud computing - the challenges of scale, complexity and change management - rather than fixating on its supposed drawbacks such as security, compliance and SLAs

• Significant growth in SaaS applications in Cloud Computing platform

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#4 - IN-MEMORY COMPUTING

“Enabling users to develop applications that run advanced queries or perform complex transactions, on very large datasets, at least one order of magnitude faster — and in a more scalable way — than when using conventional architectures”

- Gartner definition

Examples:• Fraud Detection• Price Optimization• Demand Forecast• Flight Control – Fueling, Maintenance, &

Scheduling• Simulation (What-If Analysis)

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IN-MEMORY COMPUTING

Why Now?

• 64-bit processors allowing access to 16 exabytes of memory (32-bit limited it to 4GB)

• Memory chips getting faster, more capacity, and cheaper due to Moore’s law

• New off-the-shelf commodity servers are capable of 1TB RAM capacity – big enough for many large databases to remain in memory

• In-Memory RDBMS from Oracle, Microsoft, and others allowing traditional SQL based applications to benefit immediately by placing data in memory

• New development tools making it easier for developers to build applications running across multiple blade servers

• e.g. 1000 servers – 4 cores per server with 512 GB RAM

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IN-MEMORY COMPUTING

• In-Memory Computing can squeeze batch processes normally lasting hours into minutes or seconds.

• These processes are provided in the form of real-time or near real-time services and delivered to users in the form of cloud services.

• Numerous vendors will deliver in-memory solutions over the next two years, driving this approach into mainstream use.

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#5 - ACTIONABLE ANALYTICS

• To make analytics more actionable and pervasively deployed, BI and analytics professionals must make analytics more invisible and transparent to their users

• Embedding analytic at the point of decision or action

• Real-time operational intelligence systems that make supervisors and operations staff more effective

• Provides simulation, prediction, optimization and other analytics, to empower even more decision flexibility at the time and place of every business process action

• Enabled by Big Data and In-Memory Computing technologies

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ACTIONABLE ANALYTICS

Examples:

• Improving Quality of Healthcare by allowing Physicians to make decisions based on analysis of lab results history, weight, blood pressure, heart rate monitoring feeds

• Leveraging CRM data at the point of sell (Amazon) to make smarter and better decisions

• Gaining Operational Efficiency via real-time view into data, processes, and employee productivity

• Field Service Order Processing

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#6 – SOCIAL MEDIA

• Social Media trend continues to grow and more business applications will leverage social media through integrations

• The three most trusted forms of advertising are:  Recommendations from people I know - 90% Consumer opinions posted online - 70% Branded websites - 70%

• Mobile in the middle and primary device for use of social media

• Google+ Is a Must - Google+ integration now extends to many Google properties, such as YouTube, Gmail, Blogger, and Search

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MOST USED SM TOOLS

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NEXT STEPS • Step Up. Expand your knowledge about what interests

you the most – pick 3 areas• Provoke and harvest disruption. Don’t get caught unaware

or unprepared• Look for Game Changer opportunities within your projects

through use of technologies• Keep in Mind - Your projects may not adopt or use all of

the technologies

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© 2013 KMS Technology

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