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REVOLUTIONARY BIG DATA INSIGHT ENGINE
 Anil Uberoi, Co-Founder & CEO   www.kitenga.com
 510.507.3399
 anil@kitenga.com                Kitenga: Maori, n.
                                          A perception; A view
KITENGA BIG DATA ANALYTICS PLATFORM

  First and only “Big Data” content analytics
 platform with integrated search, information
           modeling & visualization


           An entirely new kind of
           Big Data Insight Engine


   © 2012 Kitenga Proprietary                   2
THE PROBLEM: INFORMATION OVERLOAD
                                                    3rd Party
                                                    (Licensed)
                   Public data                       Data
                (Web,news, blogsphere,
                    social media)

                                Internal Data
                                (Enterprise data)


            Unstructured Data                             Structured Data




   © 2012 Kitenga Proprietary
BIG DATA= MORE THAN JUST VOLUME


                                          Volume

                                                 Newer
                                              Analytics DBs


                               Kitenga                    Traditional
                                                         DB-based BI
                                     Transform
                                 Multi-dimensional                      Velocity
                                    Big Data into
              Variety          Actionable Intelligence




  © 2012 Kitenga Proprietary                                                       4
THE SOLUTION




  © 2012 Kitenga Proprietary   5
BIG DATA (                                       ) LANDSCAPE
  Solution
  Oriented
               BI Solutions


                                          Karmasphere Analyst
               Aster Data/Teradata
               GreenPlum/EMC                  Datameer

               Vertica/HP
               VoltDB…                                                         -based Solutions
               (Analytics DBs)
                                                 Hadoop Connectors
                   Hadoop Connectors

                                        Karmasphere, Javamation… (Dev tools)



                                  Cloudera, EMC, MapR, IBM, Hortonworks…
                                                            Distributions
Programmer
  Oriented
             Traditional                                                                 Unstructured
             Structured                                                                   Big Data &
              RDBMS                                                                        Content
    © 2012 Kitenga Proprietary                                                             Analytics
KITENGA'S UNIQUENESS
   Unstructured “Big Data” content analytics
       Volume, variety/complexity, and velocity
            In addition to structured(DB) AND semi-structured data (log files)
   Business user
       Designed for non-programming/ information analyst
       Interactive information modeling and visualization
   Computational linguistics
       Machine learning, NLP, multi-lingual text analytics
   Two (Big Data related) US Patents filed

         © 2012 Kitenga Proprietary                                               7
KITENGA SWEET SPOT

       Need to exploit/monetize diverse content
            Unstructured, semi/structured content
               More than traditional BI on structured data
       Need to reduce raw data-to-insight latency
            Sophisticated/ad-hoc content analytics for
             non-programmer analysts

         Big Data = Volume*Variety *Velocity


          © 2012 Kitenga Proprietary
Kitenga Analyst

                          Kitenga                            Kitenga
                          ZettaViz                         ZettaSearch
                        Visualize, Model,                    Facetted Search,
                            Interact                           Visualization

                                             Kitenga
 Analytical                                  ZettaVox                       Analytical
 Producer                                  Crawl, Extract, NLP,             Consumer
(Information Analyst)
                                           Machine Learning,                (Business Users)
                                            Transform, Index


      © 2012 © 2011 Proprietary
             Kitenga Kitenga Proprietary
BIG DATA ANALYSIS
   Transform Big Data into Actionable Intelligence
       Aggregate
       Count
       Extract
       Transform
       Chart
       Graph
       Model
       Visualize
       Search
       Predict

        © 2012 Kitenga Proprietary                    10
UNDER THE HOOD
Critical elements include
     Natural Language Processing
     Computational Linguistics
     Machine Learning
     Document format cracking
     Segmentation
     Tokenization
     Lemmatization
     Parts-of-speech tagging
     Gazetteer lookup .
     Initial pattern recognition
     Pattern grouping
     Group disambiguation
     Etc.
       © 2012 Kitenga Proprietary   11
NEXT-GEN BUSINESS INTELLIGENCE




                                Source: James Kobielus, Feb 23,2012
                                Senior analyst for data warehousing at Forrester Research.

   © 2012 Kitenga Proprietary
NEXT-GEN BUSINESS INTELLIGENCE
                                                                               Kitenga

                                                                                      √
                                                                                      √
                                                                                      √
                                                                                      √
                                                                                      √
                                                                                      √
                                                                                      √
                                                                                      √
                                Source: James Kobielus, Feb 23,2012
                                Senior analyst for data warehousing at Forrester Research.

   © 2012 Kitenga Proprietary
.




CUSTOMER USE CASES – LIVE DEMOS
Next-gen Business Intelligence – in action

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TCS Innovation Forum 2012 - Kitenga

  • 1. REVOLUTIONARY BIG DATA INSIGHT ENGINE Anil Uberoi, Co-Founder & CEO www.kitenga.com 510.507.3399 anil@kitenga.com Kitenga: Maori, n. A perception; A view
  • 2. KITENGA BIG DATA ANALYTICS PLATFORM First and only “Big Data” content analytics platform with integrated search, information modeling & visualization An entirely new kind of Big Data Insight Engine © 2012 Kitenga Proprietary 2
  • 3. THE PROBLEM: INFORMATION OVERLOAD 3rd Party (Licensed) Public data Data (Web,news, blogsphere, social media) Internal Data (Enterprise data) Unstructured Data Structured Data © 2012 Kitenga Proprietary
  • 4. BIG DATA= MORE THAN JUST VOLUME Volume Newer Analytics DBs Kitenga Traditional DB-based BI Transform Multi-dimensional Velocity Big Data into Variety Actionable Intelligence © 2012 Kitenga Proprietary 4
  • 5. THE SOLUTION © 2012 Kitenga Proprietary 5
  • 6. BIG DATA ( ) LANDSCAPE Solution Oriented BI Solutions Karmasphere Analyst Aster Data/Teradata GreenPlum/EMC Datameer Vertica/HP VoltDB… -based Solutions (Analytics DBs) Hadoop Connectors Hadoop Connectors Karmasphere, Javamation… (Dev tools) Cloudera, EMC, MapR, IBM, Hortonworks… Distributions Programmer Oriented Traditional Unstructured Structured Big Data & RDBMS Content © 2012 Kitenga Proprietary Analytics
  • 7. KITENGA'S UNIQUENESS  Unstructured “Big Data” content analytics  Volume, variety/complexity, and velocity  In addition to structured(DB) AND semi-structured data (log files)  Business user  Designed for non-programming/ information analyst  Interactive information modeling and visualization  Computational linguistics  Machine learning, NLP, multi-lingual text analytics  Two (Big Data related) US Patents filed © 2012 Kitenga Proprietary 7
  • 8. KITENGA SWEET SPOT  Need to exploit/monetize diverse content  Unstructured, semi/structured content  More than traditional BI on structured data  Need to reduce raw data-to-insight latency  Sophisticated/ad-hoc content analytics for non-programmer analysts Big Data = Volume*Variety *Velocity © 2012 Kitenga Proprietary
  • 9. Kitenga Analyst Kitenga Kitenga ZettaViz ZettaSearch Visualize, Model, Facetted Search, Interact Visualization Kitenga Analytical ZettaVox Analytical Producer Crawl, Extract, NLP, Consumer (Information Analyst) Machine Learning, (Business Users) Transform, Index © 2012 © 2011 Proprietary Kitenga Kitenga Proprietary
  • 10. BIG DATA ANALYSIS  Transform Big Data into Actionable Intelligence  Aggregate  Count  Extract  Transform  Chart  Graph  Model  Visualize  Search  Predict © 2012 Kitenga Proprietary 10
  • 11. UNDER THE HOOD Critical elements include  Natural Language Processing  Computational Linguistics  Machine Learning  Document format cracking  Segmentation  Tokenization  Lemmatization  Parts-of-speech tagging  Gazetteer lookup .  Initial pattern recognition  Pattern grouping  Group disambiguation  Etc. © 2012 Kitenga Proprietary 11
  • 12. NEXT-GEN BUSINESS INTELLIGENCE Source: James Kobielus, Feb 23,2012 Senior analyst for data warehousing at Forrester Research. © 2012 Kitenga Proprietary
  • 13. NEXT-GEN BUSINESS INTELLIGENCE Kitenga √ √ √ √ √ √ √ √ Source: James Kobielus, Feb 23,2012 Senior analyst for data warehousing at Forrester Research. © 2012 Kitenga Proprietary
  • 14. . CUSTOMER USE CASES – LIVE DEMOS Next-gen Business Intelligence – in action