Kaushal Amin is the CTO of KMS. He had come to Vietnam in May 2013

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

2. ABOUT KMS
2
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.

3. ABOUT SPEAKER – KAUSHAL AMIN
3
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

4. 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.
4

5. INDUSTRY EXPERTS 2013 LIST
5

6. #1 – MOBILE APPS
6
• 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

7. MOBILE APPS STATS
7
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

8. #2 - BIG DATA
8
―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

9. WHAT IS GENERATING BIG DATA?
Homeland Security
Real Time Search
Social
eCommerce
User Tracking &
Engagement
Financial Services
9

10. 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
10

11. 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
11

12. 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
12

13. 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 contengency
13

14. NOSQL – SEVERAL OPTIONS
• Currently 150 implementations and growing
(http://nosql-database.org/)
• Multiple Types based on storage architecture
– Key-Value
– Document
– Column Family
– Graph
14

15. 15
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.

16. 16
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.

17. 17
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.

18. #3 - CLOUD COMPUTING
18
• 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

19. CLOUD COMPUTING
19
• 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

20. #4 - IN-MEMORY COMPUTING
20
―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)

21. IN-MEMORY COMPUTING
21
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

22. IN-MEMORY COMPUTING
22
• 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.

23. #5 - ACTIONABLE ANALYTICS
23
• 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

24. ACTIONABLE ANALYTICS
24
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

25. #6 – SOCIAL MEDIA
25
• 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

26. 26
MOST USED SM TOOLS

27. 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
27

28. © 2013 KMS Technology
Q&A