Informatica big data and social media
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Informatica big data and social media Informatica big data and social media Presentation Transcript

  • Informatica Big Data and Social Media Ramy Mahrous
  • About Informatica and Informatica Platform Informatica Integration with Hadoop and Big Data Integration Social Media Integration and Telecom Network Streaming Agenda
  • About Informatica and Informatica Platform
  • 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
  • Banking & Finance Transportation Telecom Regional Leaders Rely on Informatica
  • 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
  • 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
  • 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
  • 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
  • Informatica Integration with Hadoop and Big Data Integration
  • 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
  • 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
  • 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
  • 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.
  • Managing Metadata Informatica with Hadoop Features Hadoop lacks metadata management and data auditability Informatica supplies full metadata management capabilities Drive metadata-driven auditability
  • 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
  • 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
  • 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.
  • Informatica with Social Media
  • 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
  • Billions of social media messages Extract insights to support CRM and marketing Monitor reputation and perception Business Challenges
  • 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
  • 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)
  • 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
  • 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
  • Reaching to honest customer satisfaction about your services without surveys Customer Sentiment
  • 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
  • Sentiment Analysis Framework Illustration PowerExchange(SocialMedia Connectivity) Training algorithm to support Franco Arabic and popular expressions Remove Spam contents OLTPOLAP
  • Sentiment Analysis Dashboard
  • DEMO | Social Media Connectivity
  • Source Import – LinkedIn Pick the required source Pick the required source type People -> Get User Profiles Connection -> Get Connections for authenticated user
  • 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
  • Source Import – Facebook Pick the required source Pick the required source type Post -> Get Facebook Posts based on search
  • 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.
  • 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
  • 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.
  • 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.
  • Facebook Session Currently Public Posts are supported for searching Enter required query string to search Facebook Public Posts / Profiles for.
  • Informatica CDR Data Integration Solution
  • 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.
  • 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
  • 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
  • Thank You 