This document provides an overview and agenda for a presentation on Informatica Big Data and Social Media Integration. It discusses Informatica and its platform, integration with Hadoop and big data, social media integration, and Informatica's telecom network streaming integration solution. The document includes information on Informatica's history and partnerships, how its platform addresses traditional ETL challenges, its features for working with Hadoop and big data, and how it can be used to integrate social media data and perform customer sentiment analysis.

1. Informatica Big Data and Social
Media
Ramy Mahrous

2. About Informatica and Informatica Platform
Informatica Integration with Hadoop and Big Data Integration
Social Media Integration and Telecom Network Streaming
Agenda

3. About Informatica and
Informatica Platform

4. Informatica
• Founded: 1993
• 2011 Revenue: $784 million
• 6-year Average Growth Rate:
20% per year
• Employees: 2,554
• Partners: 400+
• Customers: 4,630
• > 70% of the Global 500
• Customers in 82 Countries
• Direct Presence in 26 Countries
• # 1 in Customer Loyalty Rankings (6
Years in a Row)
$0
$100
$200
$300
$400
$500
$600
$700
$800
2005 2006 2007 2008 2009 2010 2011

5. Banking & Finance
Transportation
Telecom
Regional Leaders Rely on Informatica

6. Informatica OEM Partners
Cloud
Analytics
Data Archiving
Financial
Services
Data Archiving
BI Solutions
SOA
Expressway
Cloud Email
Marketing
Financial
Services
Analytics
Customer
Analytics
Cloud Channel
Analytics
Enterprise
Search
Cloud Sales
Analytics
DW Appliance
Financial
Services
Health Data
Mgmt
Strategic
Service
Management
Healthcare
Solutions
BI and MDM
Supply Chain
Management
Analytics
Healthcare
Analytics
Cloud Data
Mgmt
Customer
Address
Validation
Telco Software
Solutions

7. Informatica Compatibility
OEM Partners Cloud Global SI Partners
Database and Infrastructure
BI OEM Partners Cloud Partners Global SI Partners
Database & Infrastructure
Operating Systems
Platforms & Technologies
INFORM SI Partners

8. The Tradition Approach
87% of Enterprises Use Hand-Coding for Data
Integration
Application Database Partner Data
SWIFT NACHA HIPAA …
Cloud Computing Unstructured
75% of enterprises reported
increased maintenance costs
Data
Warehouse
Data
Migration
Test Data
Management
& Archiving
Master Data
Management
Data
Synchronization
B2B Data
Exchange
Data
Consolidation
Complex
Event
Processing
Ultra
Messaging

9. Informatica Platform
Application Partner Data
SWIFT NACHA HIPAA …
Cloud Computing UnstructuredDatabase
Data
Warehouse
Data
Migration
Test Data
Management
& Archiving
Master Data
Management
Data
Synchronization
B2B Data
Exchange
Data
Consolidation
Complex
Event
Processing
Ultra
Messaging

10. Informatica Integration with
Hadoop and Big Data Integration

11. Defining Big Data
Definition: Big data is the confluence of the three trends consisting of Big
Transaction Data, Big Interaction Data and Big Data Processing
Online
Transaction
Processing
(OLTP)
Online Analytical
Processing
(OLAP) &
DW Appliances
Social
Media Data
Other
Interaction Data
Scientific
Machine/Device
BIG TRANSACTION DATA BIG INTERACTION DATA
BIG DATA PROCESSING
BIG DATA INTEGRATION

12. What influence
does she have
with her family
and friends?
How
connected
is she?
What will she
do with this
merchandise?
Any additional
services?
Big Interaction Data
Achieve a complete view with social and interaction data
Turn insights on
relationships, influences and
behaviors Into opportunities
?
Connectivity to Big Interaction
Data including social data
Databases
Call Detailed Records,
Image Files, RFIDs
External Data
Providers
Applications Customer Product …
Informatica MDM

13. Universal Data Access
Informatica with Hadoop Features
Universal
Data
Access
Structured
Semi-
Structured
Unstructured
Data Types
Conversion
Achieve ease and
reliability of pre- and post-
processing of data into
and out of Hadoop

14. Data Parsing & Exchange
Informatica with Hadoop Features
Data
Parsing &
Exchange
Images
Binaries
Industry Standards
(SWIFT, NACHA, HIPAA, etc…)
Documents
Improve productivity for
extracting greater value
from unstructured data
sources –
images, texts, binaries, in
dustry standards, etc.

15. Managing Metadata
Informatica with Hadoop Features
Hadoop lacks metadata
management and data auditability
Informatica supplies
full metadata
management
capabilities
Drive metadata-driven
auditability

16. Data Quality & Data Governance
Informatica with Hadoop Features
Data
Quality &
Data
Governance
Profile
Cleanse
Manage
Data
Promote
governance, trust and
security over siloed
activities with Hadoop
deployments

17. Mixed Workload Management
Informatica with Hadoop Features
Hadoop is not able to manage mixed
workloads according to user service-level
agreements (SLAs).
Informatica enables integration of data sets
from Hadoop and other transaction sources
to do real-time business intelligence and
analytics as events unfold.
Combine flexibility with
high data processing
power
Manage mixed workloads
and concurrency with
high throughput

18. Resource Optimization and Reuse
Interoperability With Rest of Architecture
Informatica with Hadoop Features
Informatica PowerExchange for
Hadoop with PowerCenter
RDBMSRDBMS
Informatica supports the
addition of Hadoop as
part of an end-to-end
analytics and data
processing cycle that
helps bridge the gap
between Hadoop and
your existing IT
investment.

19. Informatica with Social Media

20. Social Media
Every minute, Facebook, Twitter and
other online communities generate
enormous amounts of social media
data. If it could be tapped, it could
function like a real-time CRM
system, continually revealing new
trends and opportunities.
400 m Tweets/
day
500 m
Statuses/ day

21. Billions of social media messages
Extract insights to support CRM and marketing
Monitor reputation and perception
Business Challenges

22. Combine social data with other data sources, relational as well as
unstructured, both on premise and in the cloud
Informatica Solution for Social Media
Transformation
OLAPOLTP
PowerCenterReal-timeEdition
PowerExchange
For Hadoop
Gets Data

23. Bridge Hadoop processing environments with traditional relational database
environments to deliver the best of both worlds
Ensure cost-effective scalability, regardless of the data type or volume
Social Media
2a. Parse & Prepare Data on
Hadoop (MapReduce)
1. Load Data into Hadoop
2b. Transform & Analyze Data on
Hadoop (MapReduce)
Sales & Marketing
Datamart
Customer Service
Portal
5. Monitor & Manage (Hadoop or
non Hadoop)
4. Orchestrate Workflows (Hadoop
or non Hadoop)
3. Read & Deliver Data from
Hadoop
PowerExchange
for Hadoop
9.1 HF1
9.5 (Roadmap)

24. Enrich customer master data with social media data for a true 360-degree view
Customer
Followers
Friends
InfluencersComments
Likes
Transformation
CRM System
PowerCenterReal-timeEdition
PowerExchange
Gets Data

25. The Next Level of CRM and Marketing: social media data will enable
marketers to take their customer relationships to the next level
Powering CRM with Social Media Data: with Informatica Platform, it
becomes possible to create a single, reliable view of the customer
profile, and enrich it with data from social media interactions to gain
insights
Customer Sentiment Analysis: enables businesses to understand
customer experience and ideates ways to enhance customer
satisfaction
ROI

26. Reaching to honest customer satisfaction about your services without
surveys
Customer Sentiment

27. Extraction: Extract data from Social Networking sites
Analysis & Classification:
Cleanse & Classify
unstructured data through
machine learning algorithm
Presentation: Map social
media data to key business
parameters to deduce
actionable operations.
Customer Sentiment Process

28. Sentiment Analysis Framework
Illustration
PowerExchange(SocialMedia
Connectivity)
Training algorithm to
support Franco Arabic
and popular
expressions
Remove
Spam
contents
OLTPOLAP

29. Sentiment Analysis Dashboard

30. DEMO | Social Media
Connectivity

31. Source Import – LinkedIn
Pick the required source
Pick the required source type
People -> Get User Profiles
Connection -> Get Connections for authenticated user

32. Source Import – Twitter
Pick the required source
Pick the required source type
Entry -> Get Tweets based on search
User -> Get user profile details for given user handle

33. Source Import – Facebook
Pick the required source
Pick the required source type
Post -> Get Facebook Posts based on search

34. Twitter SessionChoose appropriate Reader
Twitter Search – Searching Tweets
Twitter User Profile – Get User profile for given twitter user handle
Enter required query string to search tweets for.
Common Operators: OR, -, #, from, to, place, @, since, until, links,
Twitter Search Examples
For complete and up-to-date details on search combinations, refer to
http://dev.twitter.com/pages/using_search.

35. Twitter Search Examples
twitter search containing both "twitter" and "search". This is the default operator
"happy hour" containing the exact phrase "happy hour"
love OR hate containing either "love" or "hate" (or both)
beer -root containing "beer" but not "root"
#haiku containing the hashtag "haiku"
from:twitterapi sent from the user @twitterapi
to:twitterapi sent to the user @twitterapi
place:opentable:2 about the place with OpenTable ID 2
place:247f43d441defc03 about the place with Twitter ID 247f43d441defc03
@twitterapi mentioning @twitterapi
superhero since:2011-05-09 containing "superhero" and sent since date "2011-05-09" (year-month-day).
twitterapi until:2011-05-09 containing "twitterapi" and sent before the date "2011-05-09".
movie -scary :) containing "movie", but not "scary", and with a positive attitude.
flight :( containing "flight" and with a negative attitude.
traffic ? containing "traffic" and asking a question.
hilarious filter:links containing "hilarious" and with a URL.
news source:tweet_button containing "news" and entered via the Tweet Button
For complete and up-to-date details on search combinations, refer to http://dev.twitter.com/pages/using_search and
http://dev.twitter.com/doc/get/search

36. LinkedIn SessionChoose appropriate Reader
People Search – Searching LinkedIn profiles
Connections – Get connections for currently authenticated user
Enter required query string to search LinkedIn Profiles for.
Common Operators: keywords, first name, last
name, company, title, school, location
LinkedIn Search Examples
For complete and up-to-date details on search combinations, refer to
http://developer.linkedin.com/docs/DOC-1191.

37. LinkedIn Search Parameters
For complete and up-to-date details on search combinations, refer to http://developer.linkedin.com/docs/DOC-1191
Parameter Definition
keywords Members who have all the keywords anywhere in their profile, including name. Use this field if you have a name that you don't know how to accurately split into a first
and last name, such as Mao Ze Dong or Jennifer Love Hewitt.
first-name Members with a matching first name. Matches must be exact. Multiple words should be separated by a space.
last-name Members with a matching last name. Matches must be exactly. Multiple words should be separated by a space.
company-name Members who have a matching company name on their profile. company-name can be combined with the current-company parameter to specifies whether the person
is or is not still working at the company.
current-companyValid values are true or false. A value of true matches members who currently work at the company specified in the company-name parameter. A value of false matches
members who once worked at the company. Omitting the parameter matches members who currently or once worked the company.
title Matches members with that title on their profile. Works with the current-title parameter.
current-title Valid values are true or false. A value of true matches members whose title is currently the one specified in the title-name parameter. A value of false matches members
who once had that title. Omitting the parameter matches members who currently or once had that title.
school-name Members who have a matching school name on their profile. school-name can be combined with the current-school parameter to specifies whether the person is or is
not still at the school.
It's often valuable to not be too specific with the school name. The same explation provided with company name applies: "Yale" vs. "Yale University".
current-school Valid values are true or false. A value of true matches members who currently attend the school specified in the school-name parameter. A value of false matches
members who once attended the school. Omitting the parameter matches members who currently or once attended the school.
country-code Matches members with a location in a specific country. Values are defined in by ISO 3166standard. Country codes must be in all lower case.
postal-code Matches members centered around a Postal Code. Must be combined with the country-codeparameter. Not supported for all countries.
distance Matches members within a distance from a central point. This is measured in miles. This is best used in combination with both country-code and postal-code.
facet Facet values to search over. Full information is below.
facets Facet buckets to return. Full information is below.
start Start location within the result set for paginated returns. This is the zero-based ordinal number of the search return, not the number of the page. To see the second
page of 10 results per page, specify 10, not 1. Ranges are specified with a starting index and a number of results (count) to return.
count The number of profiles to return. Values can range between 0 and 25. The default value is 10. The total results available to any user depends on their account level.
sort Controls the search result order. There are four options:
•connections: Number of connections per person, from largest to smallest.
•recommenders: Number of recommendations per person, from largest to smallest.
•distance: Degree of separation within the member's network, from first degree, then second degree, and then all others mixed together, including third degree and
out-of-network.
•relevance: Relevance of results based on the query, from most to least relevant.
By default, results are ordered by the number of connections.

38. Facebook Session
Currently Public Posts are supported for searching
Enter required query string to search Facebook Public Posts / Profiles for.

39. Informatica CDR Data
Integration Solution

40. Informatica Solution
Informatica CDR Data Integration Solution leverages Informatica leading data
integration platform to meet the specific needs of the telecommunications industry for
comprehensive CDR data viewing, analysis, transformation, validation, and testing.

41. Parsing and Converting CDR Data
Ensure compliance with ASN.1 standard through out-of-the-box code
generation and customized support
Parse CDR data including UMTS messages, 3GPP protocols, E-UTRAN S1
Application Protocol, and E-UTRAN X2 Application Protocol
Automate conversion of ASN.1 BER binary encoded CDR, TAP, and RAP data
into XML and ASCII
Ensure interoperability with new network equipment that generates data in
non-ASN.1 formats
GUI Tool for Message Definition, Construction, and Verification
Universal Data Transformation
Data Management, Monitoring, and Tracking
Key Features

42. Achieve end-to-end, universal data integration and transformation
Maximize strategic value of CDR data
Decrease revenue leakage from inaccurate billing, data errors, and
network changes
Identify and resolve service quality issues faster and more accurately
Identify new revenue opportunities with deeper insight into customer
behavior and trends
Benefits

43. Thank You
