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  • Primary Point Data Integration requires the use of multiple techniques. Multiple techniques involve multiple vendors today forcing the customer to deal with multiple models, management and metadata management tools. and SY aims to provide comprehensive support for all techniques with a suite, which will address the technology disparities introduced by multiple vendor solutions Details A key thing to understand is the different between techniques, technologies and products when looking at IT. Replication server is a product, Replication is a technology, Distribution is a technique and Reporting is an application. It is key to differentiate between technique and technology. In almost all data integration cases, for instance data integration for analysis use cases, customers tend to use a mix of technologies. IN this use case above what you find is the usage of ETL and Replication to stage data. Replication is preferred mechanism to stage data if you cant afford to impact the systems, if the systems are idle at night then one can run a nightly ETL job to get the data to a staging area. In the staing area one uses profiling and cleansing technologies to make the data ready for a datawarehousing before bulk loading it into the warehsouse. The reporitng tools and dashboards then leverage this sanitized data for decision making. In this architecture today, customers are forced to go to go to different vendors to get technologies for the different techniques they choose. For instance Replication is purchased from one vendor and then ETL from another. Since these come from different vendors there is no common sharing of metadata, modeling or even management. This adds to cost and complexity To address this specific issue , SY is combining its data integration technologies into a suite, such that a customer can decide on choosing a technique that is most suitable for his task without worrying about the technologies and products. Let’s take a look at the suite
  • Primary Point: Analysis in organizations require a combination of technologies but the heart of fast adhoc analysis is an analysis store. Details Let us take a look at a classic customer scenario focused on informed decision making. In many financial organizations that manage risk, today risk is managed at different levels. Each segement tends to create its own data mart, duplicating reference data and deal/market data. This duplication adds to complexity and increases the cost. So many customers are looking at creating a single datamart that will the repository of the truth, and provide access to all types of analysis engines while providing very good performance. The key requirements are adhoc analysis, complex queries, very good performance. Sybase IQ is our analysis store which meets all these requirements and significantly helps reduce cost by compressing data. In this particualr example multiple engines get to look at different views of data, while all of them leverage one common reference data. Finally a key thing with analysis is distribution of information for decision making And Sybase provides technology, today as part of our data integration capability to provide a uniform way to distribute information to myriad users and devices. let me tell you a bit more about our success in the analysis area with our IQ datastore
  • Creating an Information Edge— Today Innovative technology built upon more than 20 years of experience in creating industrial-strength information management and information mobility solutions that deliver world-class performance and reliability Open and secure software solutions that work across platforms, applications and devices High standards of business integrity toward our customers, partners, employees and competitors
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    1. 1. Informed Decision Making Shailesh Mungikar Sr. Staff Engineer, Business Intelligence Group, Sybase, Inc. Sybase Confidential Proprietary .
    2. 2. Informed Decision Making From Fairy Tale to Nightmare I absolutely need to understand how my company behaves OK guys, Let’s see how we can satisfy our users IT will analyze the problem using its own vision … We will need an ETL to store the data in our RDBMS. We will need a query tool to retrieve the data from our RDBMS. … And will use the company’s standard RDBMS Well, IT built something that works, but… … what is the exact cost of this ? The infrastructure is very expensive. We have a very few users and they complain … <ul><li>The data are not frequently refreshed. </li></ul><ul><li>The performance is low. </li></ul><ul><li>Users cannot query what they need </li></ul>
    3. 3. Information Evolution in a Data Warehouse
    4. 4. Shifting from Decisional to Operational Decisional Strategic Reports (High marginal cost per user) Pre-Planned queries Management Dashboard Operational Data Reconciliation Risk Position Fraud Detection Basel II & Regulation Compliancy Trading Cross-Selling Marketing Campaign Analysis Ad-Hoc Queries Business Performance Monitoring Operational Datawarehouse (Low marginal cost per user)
    5. 5. What does the shift mean for data warehousing technology <ul><ul><li>Business Intelligence today is mission critical. It is used to drive strategic, tactical and operational decisions. </li></ul></ul><ul><ul><ul><li>Increased query demand – predefined to ad-hoc </li></ul></ul></ul><ul><ul><ul><li>Many more users out there – 100s to 1000s </li></ul></ul></ul><ul><ul><ul><li>Reduced latency windows – overnight to intra-day </li></ul></ul></ul><ul><ul><ul><li>Increasing data volumes – data explosion to terabytes </li></ul></ul></ul><ul><ul><ul><li>Maintenance costs increasing – data volumes & administration </li></ul></ul></ul><ul><ul><ul><li>The technology supporting BI today must provide speed , scalability , flexibility and availability at a low operating cost . </li></ul></ul></ul>
    6. 6. What does it mean for IT <ul><li>The issue is about using something to do what it was designed for….. </li></ul><ul><li>Rather than starting with something that was not and creating a monster! </li></ul>
    7. 7. Informed Decision Making Data Integration Analytics Server Reporting Analytics Ad-hoc Custom Operational Systems Infrastructure for Informed Decision Making Applications to assist Informed Decision Making
    8. 8. Data Integration Using Multiple Techniques in Tandem COSMOS Smart Stream ESA Others Staging Area Data Warehouse Desktop Handheld DW Staging Tables Reporting Tools Data Mining Tools Dashboards /Portals M-Business Mobile Server WiFi GPRS Sources Star Schema Data Storage Presentation Presentation Data Acquisition Data Cleanse/ Transform Replication ETL Replication ETL ASIQ Bulk Load
    9. 9. Data Integration Suite <ul><li>Comprehensive technique coverage </li></ul><ul><li>Integrate any kind of heterogeneous data source </li></ul><ul><li>Easy to develop, deploy and maintain </li></ul>Data Integration Suite For Heterogeneous Environments Search ETL Real-Time Events Data Federation EII Replication Federation Consolidation Distribution Sybase Value Proposition Integrated Administration Integrated Modeling, Metadata and Development Available Today Available as DI Suite Q4’07
    10. 10. Typical Customer Configuration For Analysis Information Management Environment Internal Feeds External Feeds Data Sources Murex Midanz CICS-MM DLD TPS Reuters Bloomberg Users End-User Analytics Workstations Reports Laptops Mobile Computing Market Risk Credit Risk Treasury Sales Modeling & Analytics Environment Analytics Engines Risk Engines Rates Engines ETL ETL ETL <ul><li>Multiple </li></ul><ul><li>Datamarts – </li></ul><ul><li>Duplicated </li></ul><ul><li>Deal Data </li></ul><ul><li>Market Data </li></ul><ul><li>Customer Data </li></ul><ul><li>Rates </li></ul>Specialty analytics store capable of handling large volumes of data and servicing in real-time complex queries for risk management <ul><li>Single Risk </li></ul><ul><li>Datamart: </li></ul><ul><li>Deal Data </li></ul><ul><li>Market Data </li></ul><ul><li>Customer Data </li></ul><ul><li>Rates </li></ul><ul><li>Calculated Values </li></ul>Information delivery to heterogeneous users and devices Information Delivery Multiple users of datamart with different views all accessing same reference data Extract / Transform / Load (ETL) Tool Information Delivery
    11. 11. What is Sybase IQ? <ul><ul><li>Sybase IQ is a highly optimized analytics server, designed specifically to deliver ultra-high-speed business intelligence & reporting on standard hardware and operating systems </li></ul></ul><ul><ul><li>It delivers for today’s operational BI needs … </li></ul></ul><ul><ul><li>high speed data loads for analytics </li></ul></ul><ul><ul><li>exceptional query performance </li></ul></ul><ul><ul><li>ad hoc query performance up to 100x faster than a row based RDBMS </li></ul></ul><ul><ul><li>dramatically lower TCO by reducing performance overhead, storage costs & maintenance requirements </li></ul></ul>“ Sybase IQ stores data very efficiently , produces results much faster and puts less pressure on our processors. It gives us great capacity to accommodate growth .” - BNP Paribas
    12. 12. Hong Kong Housing Society <ul><li>SOLUTION </li></ul><ul><li>Sybase IQ, Sybase ECDA </li></ul><ul><li>RESULTS </li></ul><ul><li>93% reduction in data preparation time for BI reporting </li></ul><ul><li>Up to 70% data storage saving </li></ul><ul><li>Report generation is 16x faster </li></ul><ul><li>CHALLENGE </li></ul><ul><li>Extraction and transformation of data from ERP system data takes takes more than 24hrs </li></ul><ul><li>Instead of daily, batch reporting run limited to twice a week </li></ul>
    13. 13. JDE SAN Mirror DW Database DW Database Hong Kong Housing Society Architecture 16 x Faster Over 30 hours Prod DB 11 GB Within 2 hours Prod DB 3 GB
    14. 14. Internal Revenue Service (USA) <ul><li>CHALLENGE </li></ul><ul><li>Needed a data management and analytics system to supply users across the country with relevant, timely and accurate data, amassing up to 10 years of business and individual return raw data. </li></ul><ul><li>RESULTS </li></ul><ul><li>Delivers standardised data in an integrated environment for decision making </li></ul><ul><li>Reduces load and maintenance times </li></ul><ul><li>Provides 70 percent compression rate </li></ul><ul><li>Delivers three to five times faster query responses </li></ul><ul><li>Easy to manage </li></ul><ul><li>SOLUTION </li></ul><ul><li>Sybase IQ, Sybase ASE </li></ul>
    15. 15. Compliance Data Warehouse Infrastructure Database Server (Sybase IQ) Application Server (SAS, SAS Enterprise Miner, Hyperion Intelligence) Shared Storage (72 Terabytes) IRS Network IRS Network SPSS Access SQL Hyperion SAS
    16. 16. US Securities and Exchange Commission Mission Critical Analytics <ul><li>CHALLENGE </li></ul><ul><li>Need a more efficient means to provide disclosure of important securities information </li></ul><ul><li>Needed a more efficient means to ensure securities laws </li></ul><ul><li>RESULTS </li></ul><ul><li>New data warehouse built in less than 12 months </li></ul><ul><li>25% reduction in “off hour” data loads </li></ul><ul><li>35% improvements in query response time </li></ul><ul><li>The ability to create and run more complex queries </li></ul><ul><li>Disaster recovery capabilities with under 1 minute failover </li></ul><ul><li>No unplanned down time </li></ul><ul><li>Now incorporates documents and emails (unstructured data) into analysis with structured data </li></ul><ul><li>Accommodates future growth </li></ul><ul><li>SOLUTION </li></ul><ul><li>Sybase IQ, Sybase ASE </li></ul>
    17. 17. Sybase, Inc. <ul><li>Creating an Information Edge — Today </li></ul><ul><ul><li>Open, cross-platform software solutions that securely deliver information anytime, anywhere </li></ul></ul><ul><ul><li>Strongest portfolio of information management and enterprise mobility solutions in the market </li></ul></ul><ul><ul><li>The world’s most critical data in commerce, communications, finance, government and healthcare runs on Sybase </li></ul></ul><ul><ul><li>~4,000 employees in 60 countries </li></ul></ul><ul><ul><li>Profitable and growing </li></ul></ul>Sybase is the largest global enterprise software company exclusively focused on managing and mobilizing information , from the data center to the point of action.