Data Analytics Challenges in Data Growth and Information Distillation Deepak Ramanathan Head - Technology Practice Asia Pa...
Anticipate & Manage Change
Enterprise Information:  Doubling at an Unprecedented Rate <ul><li>Falling storage costs continue to drive the appetite fo...
The Data Explosion <ul><li>In 2009, despite the global recession, digital data grew by 69% to 800,000 petabytes </li></ul>...
Key Challenges for Data Management <ul><li>Growth in embedded systems for </li></ul><ul><ul><li>Smart Grid </li></ul></ul>...
What makes up this Data Explosion?   Structured data  Relational databases, structured data files, system/application data...
Après Structured Data – The Deluge !
Top Predictions for Business Analytics* <ul><li>Social </li></ul><ul><li>Self service </li></ul><ul><li>Pervasive </li></u...
Social <ul><li>&quot;We have the ability to run an open, transparent, participatory and collaborative government.”  1 </li...
 
Enhancing Public Services with insights  from Gov 2.0 Text Analytics <ul><ul><li>Improving Staff Productivity </li></ul></...
The InDatabase Approach – Scale  SAS Scoring Data EDW Traditional Capabilities Data Teradata EDW  SAS In-Database Capabili...
Pervasive Computing
Pervasive Analytics
Cloud is here.. Grid Manager Distributed Enterprise Scheduling Workload Balancing Parallelized Workload Balancing Distribu...
Key to Building Analytical Solutions <ul><li>Collaborating with interdisciplinary teams that combine </li></ul><ul><ul><li...
SAS Innovation Continues <ul><li>Solving challenging problems for our customers using the analytical tools directly  </li>...
Thank you  Enjoy the conference
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SUNZ 2011 - SAS Business Analytics

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  • Talking Points No matter what we do, no matter how we live our lives, no matter where we work…we are all feeling changes in the global marketplace—certainly from an economic perspective. The way in which we are doing business today and will do business in the future is very different from the way we have done business in the past. What has made our organizations successful is most likely not what will make them successful in the future. One thing is certain: the ability to anticipate and manage change—using data to support proactive decision making—is more important than it has ever been.
  • http://www.computerworld.com/s/article/9129043/New_federal_CIO_Vivek_Kundra_wants_a_Web_2.0_government?taxonomyId=69&amp;pageNumber=2 Polling on Facebook Sites
  • 10,000 to 50,000 tweets at any hour mentioning “Iran”, it peaked yesterday at 221,744. This seems extreme, but it makes sense when you realize that it corresponds with when Twitter’s downtime was rescheduled, which had major buzz the entire day. We’re approaching one million tweets on the situation, if we haven’t passed that number already. Heck, it’s been 1% of all Twitter chatter In the last 24 hours, 2,250,000 posts were published. And while news stories within Google News have risen dramatically as well, they don’t hold a candle to the social media buzz
  • Copyright © 2010, SAS Institute Inc. All rights reserved.
  • SUNZ 2011 - SAS Business Analytics

    1. 1. Data Analytics Challenges in Data Growth and Information Distillation Deepak Ramanathan Head - Technology Practice Asia Pacific
    2. 2. Anticipate & Manage Change
    3. 3. Enterprise Information: Doubling at an Unprecedented Rate <ul><li>Falling storage costs continue to drive the appetite for higher data volumes and data stores, including transactional systems; office automation and collaboration; LAN file systems; databases and warehouses/marts; e-mail, instant messaging, wikis, blogs, voice; digital images, video, RFID, etc. </li></ul>2005 1,100 days 2007 11 months 2010 11 hours
    4. 4. The Data Explosion <ul><li>In 2009, despite the global recession, digital data grew by 69% to 800,000 petabytes </li></ul><ul><li>In 2010, the Digital Universe grew almost as fast to 1.2 zettabytes </li></ul><ul><li>By 2020, the data will be 44 times as big as in 2009 </li></ul>
    5. 5. Key Challenges for Data Management <ul><li>Growth in embedded systems for </li></ul><ul><ul><li>Smart Grid </li></ul></ul><ul><ul><li>RFID </li></ul></ul><ul><ul><li>Telemetry data from automobiles </li></ul></ul><ul><li>How much data do you keep? </li></ul><ul><li>What data do you keep? </li></ul><ul><li>How quickly can you access data? </li></ul><ul><li>How do you distill information from this data? </li></ul><ul><li>How do you analyze this data? </li></ul>
    6. 6. What makes up this Data Explosion? Structured data Relational databases, structured data files, system/application data and logs that reside in a data store, defined by a catalog (table definitions)/data model accessible via SQL or Object definitions. This data has a characteristic of being contextualized by the heading (field name) and possibly defined in relation to other &quot;fields.” This data is also capable of being processed in a simple manner, summed or aggregated, etc. Semistructured Data houses structure with freeform elements (e.g., e-mails) and has structure and context to specific elements in the header, but is freeform text in the body.. Unstructured data Most of the information that resides in organizations is unstructured in nature – images, content of Web documents, standard documents, audio, video and correspondence. This type of information is typically difficult to find effectively if nothing has been done to make the data accessible, such as putting it into a content management system and tagging it with metadata . 70% 25% 5%
    7. 7. Après Structured Data – The Deluge !
    8. 8. Top Predictions for Business Analytics* <ul><li>Social </li></ul><ul><li>Self service </li></ul><ul><li>Pervasive </li></ul><ul><li>Scalable </li></ul><ul><li>Cloud, and </li></ul><ul><li>Real-time </li></ul><ul><ul><li>James Kobielus, Forrester Research </li></ul></ul>
    9. 9. Social <ul><li>&quot;We have the ability to run an open, transparent, participatory and collaborative government.” 1 </li></ul>
    10. 11. Enhancing Public Services with insights from Gov 2.0 Text Analytics <ul><ul><li>Improving Staff Productivity </li></ul></ul><ul><ul><li>Increasing Operational Efficiency </li></ul></ul><ul><ul><li>Collaboration & Exchange </li></ul></ul><ul><ul><li>Leveraging the Power of Technology </li></ul></ul><ul><ul><li>Caring for the Environment </li></ul></ul><ul><ul><li>Delivering Social Care </li></ul></ul><ul><ul><li>Improving Citizen & Business Service Delivery </li></ul></ul><ul><ul><li>Improving Compliance & Accountability </li></ul></ul><ul><ul><li>Raising Standards in Education </li></ul></ul>
    11. 12. The InDatabase Approach – Scale SAS Scoring Data EDW Traditional Capabilities Data Teradata EDW SAS In-Database Capabilities SAS Analytic Modeling SAS Analytic Modeling SAS Scoring Data Modeling Preparation
    12. 13. Pervasive Computing
    13. 14. Pervasive Analytics
    14. 15. Cloud is here.. Grid Manager Distributed Enterprise Scheduling Workload Balancing Parallelized Workload Balancing Distribute parallelized workloads to a shared pool of resources. Distribute workloads to a shared pool of resources. Distribute jobs within workflows to a shared pool of resources. Optimize the Efficiency and Utilization of Computing Resources
    15. 16. Key to Building Analytical Solutions <ul><li>Collaborating with interdisciplinary teams that combine </li></ul><ul><ul><li>Industry experience </li></ul></ul><ul><ul><li>Specialized software development skills for data management, analytical computing, reporting </li></ul></ul><ul><ul><li>Expertise in in statistics, data mining, forecasting, optimization </li></ul></ul><ul><li>Understanding complex data </li></ul><ul><li>Synthesizing effective analytical algorithms </li></ul><ul><li>Building models that work with large volumes of data </li></ul><ul><li>Evaluating the performance of models </li></ul>
    16. 17. SAS Innovation Continues <ul><li>Solving challenging problems for our customers using the analytical tools directly </li></ul><ul><li>Working closely with the analytical solutions in vertical domains which provide increasingly challenging problems in terms of scale and complexity </li></ul><ul><li>… Responding to multiple challenges </li></ul>
    17. 18. Thank you Enjoy the conference

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