Overcoming the 5 Biggest Challenges in Data Mart Consolidation


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Discussing the steps you can take now to migrate and consolidate low performing data marts – each with their own data models - onto a new high-performance platform managed by a high quality data foundation for analytics that both business and IT can use.

Watch the webinar replay at www.kalido.com/5-challenges-of-data-mart-consolidation.htm

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  • Hello everyone and welcome to our webinar “Overcoming the 5 biggest challenges in data mart consolidation”. My name is John Evans, I’m the Director of Product Marketing at Kalido, and I will be the moderator and a speaker on today’s webinar.
  • Before we begin today’s presentations, I’d like to review a few logistics. Our webinar will last approximately 60 minutes. The webinar will be recorded and made available for replay. Attendees will be muted during the call. However, you may submit questions at any time during the broadcast using the chat box in the Go-to-Webinar control panel. We’ll answer as many questions as time allows.  We’ll be tweeting about the webcast today, so please join in the conversation using hashtagkalido, and follows us @kalido. Also, just to pre-empt the question we always get: yes, slides will be available after the webcast so if you’d like a copy please send us an email.
  • Today I have two guests who will join me to discuss our topic, and they are Patrick Mullins from Oracle, and Lovan Chetty from Kalido. Patrick is a Master Principal Sales Consultant with Oracle Corporation.  He has over 20 years experience working with Oracle Products and specializes in data warehousing, database performance and Oracle Exadata. Welcome Patrick. (PATRICK SAYS: Thanks, John. Nice to be here) I’m also joined by Lovan Chetty, who is Senior Manager of Product Management at Kalido and has been with Kalido in various roles in product management and implementation consulting for many years, so he has very deep knowledge and insight into not only how Kalido works, but how customers use it and will provide us some technical insight into our topic today. Welcome Lovan. (Thanks John)
  • Today’s session is about data mart consolidation. We’ll start with a high level overview of the issues companies face when migrating and consolidating data marts, and mention the top 5 challenges, then we’ll talk about how Kalido can address those challenges. We’re launching a new version of our product today which is key to meeting these challenges, and Lovan will be showing us a short demo to give you an idea of how we can tackle this problem. As part of our product launch we’re supporting Oracle Exadata, so we’ll talk to Patrick about some of the key attributes of the Oracle Exadata Database Machine that make it appropriate for such a consolidation. We welcome your questions throughout our discussion. So, at any time during the webcast please type in your questions in the chat box.But to learn more about you, let’s do a quick POLL: I’m interested in DMC because:
  • Now, data mart consolidation has been around as a problem for a long time, so why are is this important to talk about now?First is the fact that there are so many and it is a pervasive problem. On research study found that 59% of companies run upwards of 30 data marts across their organization, and some companies had more than 100 marts.Second, they are expensive to maintain - A Gartner Research Report states that consolidation makes sense for many reasons:The cost to maintain a data mart is between $1M and $2M. These costs include multiple Extraction, Transformation, and Loading (ETL) processes, software licenses and maintenance, storage and server hardware, and personnel.Gartner further Estimates that 35% and 70% of these costs are redundant across data marts.The other main reason is because there are pretty big benefits that can come from consolidating or migrating marts to new environments, mainly in service for better data for the business, and an ability to expand those consolidated or migrated marts into new areas that can cover new data sources and new requirements from the business.And of course there is a benefit for IT. As we’ve just seen it is expensive to maintain this environment, and there is no control over a shadow IT environment of independent data marts spread across an organization.Gartner doesn’t see this going away – in fact last year they predicted that marts will continue to proliferate, and that IT needs to plan for ongoing consolidation and come up with a strategy.So let’s do a quick POLL: how many data marts do you have to consolidate?But how do you approach this?
  • Most would say it is a matter of building a data warehouse, or an enterprise data warehouse, and bringing in those marts.And how do we build warehouses? Most would start with the traditional approach, using a set of modeling tools and integration tools to build them.But these tools aren’t agile enough to deliver in a timely way.So consider this scenario: some business event occurs, and then data needs to be collected, analyzed, modeled, integrated, set up in BI tools, tested and rolled out. In a situation with required data in many marts, the requirements and analysis phase may be significant, then there is the integration work.This all takes time, and the longer it takes, the longer the organization waits to make a decision. As time goes on, the value of that decision diminishes. For example, if your decision could cut costs, you’re still paying them until you figure out what to do. If it is a revenue-generating opportunity, you’re not earning that revenue until much later than you would like. So there is a business benefit that is lacking.
  • What you really need is a way to shorten the cycle to make decisions in order to maximize that business value, whether it is to stop spending as soon as possible or it is to start selling as soon as possible. So the idea is to move up the curve to the left to shorten the time to value so you maximize the business value benefit.So thinking about migrating and consolidating data marts, you’re going to have to go through these steps, and for potentially EACH mart you want to consolidate.So let’s look at a couple of options that you might consider when migrating and consolidating marts.
  • The first is to acquire a new high performanceplatform and just move your mart from your current environment to your new one, sometimes called a lift and shift. In this scenario you simply lift your current mart, and move it, unchanged, to faster hardware.What you get is better query and user response speed, and better data load speeds to handle growing volumes of the data that is in those marts.<CLICK>However, they are unchanged. They may still be brittle and difficult to morph into a mart that reflects current needs. There is no additional agility you gain from doing this. And there is nothing that makes it easier to rip out time and effort from the steps we just discussed, to help you move up that curve.So you end up with the same hairball but on faster, shinier hardware.
  • A second approach is to go for an EDW. In this approach you need to spend a bunch of time modeling out the new warehouse. You’ll likely take a traditional approach use your traditional modeling tools, integration tools and waterfall-style approach to building the EDW. The activity of building the new schema is a do-over. You’ll want to use your existing marts as a starting point, but you need to analyze them and re-architect them. And if you have a lot of marts like some of you said you did, that is going to add to the amount of time it takes to get that EDW rolled out into production.<CLICK>So while you will eventually get there, that is just the issue – how long until “eventually.” It might take months or worse, years, before you are able to deliver value to the organization.
  • So there needs to be a better way, and that’s what we are discussing and proposing today.You still should migrate your marts to a new high performance platform. There is a lot of benefit to be gained from this not only initially in terms of query and load speed, but also over the long term as the data volumes grow.You should look at agile tools instead of your traditional hand-coded ETL tools and start-from-scratch modeling tools. The new release of Kalido that we announced today exploits your existing mart models and allows you to create a business information model that is conceptual, and that enables reverse engineering, so you can more efficiently analyze and architect the warehouse.This is going to make it easier for you to focus on refactor the model to get the warehouse designed quickly and more completely so you spend more time focusing on addressing business problems to be analyzed from your warehouse, instead of wrestling with the technology behind it.I mentioned the speed and performance benefits of using a high performance platform, but that other benefit of that is that not only can you manage increasing data volumes of your current mart contents, but also you’ll be able to easily handle more data coming from more sources to handle new requirements that you add to the consolidated warehouse.CLICKNow, there is no requirement to wait for the entire DW to be built before you begin delivering access to your users. You can roll in one mart, then another, then another, incrementally updating the new model. This approach allows you to deliver business value sooner, retire old marts as you go, and have it built on a much more agile foundation.Time for one more POLL: which best describes your DMC status?
  • So that is my recommendation. But there are still challenges to overcome in any mart consolidation or migration initiative.How exactly can you reuse existing data mart models, and how to you refactor them to bring them up to current requirements, and share those models with business users so they can participate in the redesign?What do you do about all the data integration and ETL jobs you’ve got set up to feed those marts – how will you get the existing data into the new warehouse?What do you do about data duplication when you’re bringing in multiple marts?How do you ensure referential integrity as you refactor?How do you control costs associated with this effort, making sure you have a platform that supports future growth, and that you don’t blow out your budget on consultants writing code to deliver the consolidation or migration?
  • Well, today Kalido announced a new version of the Kalido Information Engine, and there are some new features that are specifically added to address these challenges and complement what we’ve already done in terms of reducing the need for third party data integration tools in this effort. What IT can now do is take an existing model, either in CSV or in CWM 1.x format, and load it into BIM. What they get is a conversion that includes all the gnarly labels from the source model, whether a logical or a physical model.What you can then do is reverse engineer it to build it out and organize it into a business model that beings all the benefits of our business model to the business.But in this state with lots of consonants, no vowels and lots of underscores, a business person can’t read it. So name and label management is critical. So in SP1, BIM can take your business glossary that has a key of all the IT terms translated into complete words, and makes the conversion. Now you’ve very quickly come up with a standard business model we all know and love. A key benefit is the customer didn’t have to start from scratch. So thinking about data marts that have these models already in place, customers can now exploit them to build business models in the agile KIE.
  • Lovan, thanks for that great overview.So what you just saw was the business model…Clickand some of the automationkalido provides for modeling and data integration.ClickKalido also automates a number of other areas includes BI delivery, testing and RTPour automation touches all these areas – making the architecture therefore simpler, easier and less expensive to maintain and to deliver business value faster.This model-driven automation is a huge benefit to the development team that struggles to deliver value using traditional methods to satisfy business needs because these things must be handled manually.
  • As customers will likely consider new high performance platforms for this activity, we’ve added another one – Oracle Exadata.Kalido is tuned and optimized for Exadata out of the box.Initial testing delivered performance gains of 4-50 times over traditional relational databases and significant improvement over other high performance platforms. Oracle’s combination of smart storage software and industry-standard hardware delivers faster parallel processing. Running on Exadata, the Kalido Information Engine reduced data load times by more than two-thirds without the need for tuning or manual optimization.Existing Oracle customers can now seamlessly migrate from Oracle 11g implementations to Kalido running on Exadata. TRANSITION:So, now I want to bring Patrick Mullins from Oracle into the discussion. Patrick, can you tell us a little bit about Oracle Exadata
  • ORACLE EXADATA DATABASE MACHINE slide – PatrickTransition: John: Patrick, how do you fit all this capability on to one machine?
  • EXADATA ARCHITECTURE slide – Patrick Transition: John: So we say some very impressive performance on our internal testing, what does Exadata do to accomplish this?
  • EXADATA INNOVATIONS slide – Patrick Transition: john: Patrick can you give me an example of how you measure performance? 
  • SQL QUERY INPUT slide – Patrick Transition: john: How does Exadata easily accomplish consolidation, and what does that workload look like on the Exadata platform?
  • EXADATA DELIVERS EXTREME CONSOLIDATION slide – Patrick Transition: John: I talked earlier about moving up the curve to reduce the time spent on various steps to deliver mart consolidation and new warehouse development. How does Exadata help customers achieve this result?
  • PRE-OPTIMIZED OUT OF THE BOX slide – Patrick Transition: John: Patrick that’s great. Can you summarize the Exadata difference?
  • THE EXADATA DIFFERENCE slide - Patrick
  • Here’s one quick example of a customer who has selected Kalido on ExadataIndependent Health, a leading regional based health insurance provider has selected the Kalido Information Engine High Performance Platform Edition and will deploy it on the Oracle Exadata Platform.Independent Health has been seeking to reduce costs through improved analysis of market conditions, more efficient identification of fraud as well as to advance its pioneering efforts to meet market demands and provide high-quality, affordable health coverage. Independent Health realized they would need to dramatically increase both the scale and performance  of their data warehousing environment in order to get the best answers needed to improve their competitive edge.After extensive evaluation of leading high-performance data warehouse platforms Independent Health selected Kalido on Oracle Exadata because of a dramatic improvement in performance, scalability, extensibility and seamless migration and compatibility with their existing 11G-based data warehouse.Independent Health developed their Enterprise Data Warehouse with the Kalido® Information Engine™ to replace a traditional ETL-based system. With Kalido, Independent Health can better contain operating costs by more effectively managing data related to members, providers and claims. Independent Health will be discussing this in more detail on a webcast on February 7, so please attend that event to learn more.
  • So, I’ll summarize what we talked about today and how you can get started on a mart consolidation and migration project. After discussing the issues we heard about some new capabilities in Kalido that enable meeting these top challenges, and Lovan showed you a demonstration where he was able to reuse an existing data mart, bring it into the Kalido environment, and refactor the model to reflect current requirements; then he showed how he loaded data from an existing mart source and quickly defined the proper integration mappings and handle duplicated data; and you saw how easy it was during the refactoring step to maintain referential integrity throughout the process and how the Kalido Information Engine reads the model and uses those relationships to manage all the associations. And finally, we heard from Oracle and looked at a customer example on how running Kalido on Exadata can bring costs under control while delivering better performance, as well as witnessing automation in Kalido that further reduces costs, and you saw how the model can be changed to accommodate future changes.
  • Together, the new Kalido capabilities coupled with our recent innovations in ripping out time and effort in the data integration area, plus running on a high performance platform like Exadata, you can see how there are ways to move up that curve by taking time and resources out of these key steps to deliver better business value sooner, so your business users can make the critical decision they need to keep your business competitive.
  • This graphic shows the Kalido time-to-value zone, and the advantages Kalido brings compared to the traditional data warehouse approach using traditional tools.While we only covered details on the modeling and design areas today, you can check out our website and learn more about how we address the data integration and data access activities as well as their implications on testing and release to production.
  • So I’ll leave you with the benefits for the two main groups involved in data mart consolidations and migrations.For IT, it’s about better control and governance over the analytics used across the organization, and a way out of the shadow IT scenario.The capabilities we discussed today can accelerate a consolidation project.Which will give you better responsiveness to what the business demands.And the Kalido automation and consolidation on high performance platforms like Oracle Exadata will reduce TCO.For the business: you’ll get better information faster to use in your day to day analytical activities, with the confidence that IT is setting you up on an information management foundation that will enable you to become an agile business.
  • So with that let’s turn to Q&A
  • John: OK that’s about all the time we have for today’s event. As far as next steps for our audience, here are some things you can read and do to learn more and to network with other Kalido customers.First, everyone will receive a copy of our new white paper entitled The Next Gen of DI for DW which discusses how Kalido delivers faster time to value compared to traditional warehouse development approaches. Don’t forget to tune in to the webcast with independent health on Feb 7 to learn more about how a mid-sized organization is dealing with a rapidly changing information landscape and the need for better information. And to read more from Kalido on this and other topics, you can check out my blog that is specific to the KIE, you can follow @kalido on twitter, and you can join the Kalido Connections community, which is also accessible from Kalido.com You can always reach us via telephone, too. Well that’s it for today, thanks to our panelists Patrick Mullins from Oracle and Lovan Chetty from Kalido. Thank you for attending.  
  • Overcoming the 5 Biggest Challenges in Data Mart Consolidation

    1. 1. Overcoming the 5 Biggest Challenges in Data Mart Consolidation Kalido Webcast January 31, 20121 February 15, 2012 Kalido © I Kalido Confidential I February 15, 2012
    2. 2. Logistics Attendees will be on mute for the call Type your questions into the Questions box Webcast is being recorded and will be available for replay Request a copy of today’s slides by sending an email to: marketing@kalido.com Join the conversation online by using the #Kalido hashtag. Follow us @kalido !2 February 15, 2012 Kalido © I Kalido Confidential I February 15, 2012
    3. 3. Today’s Speakers John Evans Director of Product Marketing, Kalido Patrick Mullins Master Principal Sales Consultant, Oracle Lovan Chetty Senior Manager, Product Management, Kalido3 February 15, 2012 Kalido © I Kalido Confidential I February 15, 2012
    4. 4. Discussion Topics Data Mart Consolidation Issues The 5 Challenges How Kalido and Oracle Exadata Enable Data Mart Consolidation Q&A4 February 15, 2012 Kalido © I Kalido Confidential I February 15, 2012
    5. 5. Why Data Mart Migration & Consolidation? Data marts are expensive and spread across the organization – 59% of companies maintain up to 30 data marts – $1.5 – $2 million annually to maintain a single mart – 35% – 70% of those costs are redundant Customers can improve information consistency, create more complete analytics and save moneyCIOs should be aware that data marts will emerge continuously in theorganization. They should advise the business intelligence and datawarehouse teams to plan for ongoing data mart consolidation and demandthat a strategy for accomplishing it is in place. -- Gartner, Data Warehousing Trends for the CIO, 2011-20125 February 15, 2012 Kalido © I Kalido Confidential I February 15, 2012
    6. 6. Traditional Warehousing Takes Too Long Business ValueTraditional Time to Deliver 6 February 15, 2012 Kalido © I Kalido Confidential I February 15, 2012
    7. 7. Shorten the Cycle, Maximize Business Value Business Value Kalido Business Value Benefit Time to Value BenefitTraditional Time to Deliver 7 February 15, 2012 Kalido © I Kalido Confidential I February 15, 2012
    8. 8. Mart Consolidation Options: Lift and Shift Migrate existing marts onto a high performance platform Same poorly- Improve query speed and constructed and end-user response time inflexible marts, just Manage increasing volumes running on a faster of existing data platform8 February 15, 2012 Kalido © I Kalido Confidential I February 15, 2012
    9. 9. Mart Consolidation Options: Integrate into EDW Migrate existing marts onto a high performance platform Same poorly- Improve query speed and constructed and end-user response time inflexible marts, just Manage increasing volumes running on a faster of existing data platform Use traditional tools and approach to merge marts Significant time to analyze No value delivered and re-architect for months or longer Diversity of marts can lengthen time to build9 February 15, 2012 Kalido © I Kalido Confidential I February 15, 2012
    10. 10. Ideal Approach to Mart Consolidation Migrate existing marts onto a high performance platform Use agile tools and approach to merge marts Consistently deliver Exploit existing assets to business value as you accelerate reverse engineering build the Focus on solving business warehouse, retiring problems, not overcoming technical hurdles marts as you go, on an Improve query speed, end- agile foundation for user response and load time future growth Manage increasing volumes of existing and new data10 February 15, 2012 Kalido © I Kalido Confidential I February 15, 2012
    11. 11. Top 5 Challenges Reusing existing mart assets and refactoring the model Untangling all the data integration connections Data duplication between and within marts Referential integrity Controlling costs and preparing for change The number of data migration and conversion projects is on the increase as organizations focus on IT modernization, cost optimization and merger/acquisition initiatives. -- Gartner, Risks and Challenges in Data Migrations and Conversions11 February 15, 2012 Kalido © I Kalido Confidential I February 15, 2012
    12. 12. New Modeling & Design Improvements Exploits your current logical and physical models and taxonomies to build a new more agile data warehouse Enables reverse engineering Converts technical names and labels to business- friendly terms – Leverages existing business glossary and abbreviations document12 February 15, 2012 Kalido © I Kalido Confidential I February 15, 2012
    13. 13. Demo13 February 15, 2012 Kalido © I Kalido Confidential I February 15, 2012
    14. 14. What You Will See Read a physical model from an existing data mart Refactor the model into a business information model Deploy the model Initial population of the model from existing data mart14 February 15, 2012 Kalido © I Kalido Confidential I February 15, 2012
    15. 15. Kalido Enables Delivery In 90 Days or Less Modeling Data Integration Star and Snowflake Schema Data Sourcing and Field Mapping Code Management and Lookup Testing Physical Schema Management Delta Detection Suspense and Exception Handling Built-in Integrity Checking Slowly Changing Dimensions Data Validation Currency and Units of Measure Aggregate Task Results System Key Management Contra Processing Data Mart and Aggregates Excel Integration for User reconciliation Data Export & Purging Post Processing HousekeepingData Load and Index Management Data rollback and batch reload for system test Rollup Path Awareness User Interface for data browsing & Business Information Model Driven Automation troubleshootingIncremental Summary Generation Convert Existing Logical Models Name & Label Management Release to Production Version Management BI Delivery Object level Change Management Native QlikView GenerationNative XLS Pivot Table Generation Model Migration Operations Generic Export/ Import for Data MigrationMetadata Management for COGN Task Execution & Monitoring Process AutomationMetadata Management for BOBJ Object Level Dependency Deployment and Migration Archiving for Migration VersionsMetadata Management for MSAS Restore for Model and Data Undo Loads Model Comparison ReportReport-Time Formula Management Audit and Logging Job Definition with Dependency 15 February 15, 2012 Kalido © I Kalido Confidential I February 15, 2012
    16. 16. Oracle Exadata Support Combines Kalido’s business-driven automation with Exadata’s extreme data warehousing performance Tuned and optimized out-of-the-box Record performance for Kalido on any platform to date – 4 to 50 times faster vs. traditional relational databases – Significantly faster than other high- performance platforms Unparalleled time-to-value for any data warehouse project16 February 15, 2012 Kalido © I Kalido Confidential I February 15, 2012
    17. 17. Oracle Exadata Database Machine One architecture for… • Data Warehousing • OLTP • Database Consolidation Exadata is Oracle’s strategic database platform for ALL Oracle Database workloads17 | © 2011 Oracle Corporation |
    18. 18. Exadata Architecture A complete system: compute, storage, networking • Database Cluster – Intel-based database servers – Oracle Linux or Solaris 11 – Oracle Database 11g – 10 Gig Ethernet (to data center) • Storage Grid – Intel-based storage servers – Up to 504 terabytes raw disk – 5.3 terabytes Flash storage – Exadata Storage Server Software • InfiniBand Network – Internal connectivity ( 40 Gb/sec )18 | © 2011 Oracle Corporation |
    19. 19. Exadata Innovations• Intelligent storage • Hybrid Columnar Compression – Scale-out InfiniBand storage – 10x compression for warehouses – Smart Scan query offload – 15x compression for archives uncompressed + + + Data remains compressed compress• Smart PCI Flash Cache for scans and – Accelerates random I/O up to 30x in Flash primary DB – Triples data scan rate Benefits Cascade to Copies standby dev test backup 19 | © 2011 Oracle Corporation |
    20. 20. SQL Query Throughput 75 Query Throughput Gigabytes per Second 25 11 * 50,000 1,500,000 9 IOPS IOPS (I/Os per second) 6 2.5 IBM XIV NetApp 6080 IBM DS8700 Hitachi USP V EMC VMAX Exadata Disk Exadata Flash * Undisclosed by vendor20 | © 2011 Oracle Corporation |
    21. 21. Exadata Delivers Extreme Consolidation • Large Memory – Many databases can be consolidated • Extreme Performance – OLTP, DW, data mining, batch, reporting, loading, backups, files in the database – Encryption, compression • Workload Management – Manage SLAs via Quality of Service (QoS) – CPU and I/O resource management – Instance caging Shrink data center costs, increase system utilization and promote application integration21 | © 2011 Oracle Corporation |
    22. 22. Pre-built and Optimized Out-of-the-Box 100% Custom Configuration Test & debug failure modes Performance Achievement Performance Achievement Measure, di agnose, tun e and Multi- Assemble reconfigure vendor dozens of finger components pointing Time Time (Days) (Months)22 | © 2011 Oracle Corporation |
    23. 23. The Exadata Difference Exadata DB Machine Custom Configuration  Storage scans & filters data Storage just ships blocks  Storage offloads DB* DB-unaware storage 168 CPU  Flash caches relevant data No DB-aware flash managementcores instorage  40 Gb/sec network 8 – 10 Gb/sec network  Pre-built for DB workload Assembled by customer  Redundancy built-in Build-your-own HA  Compression built-in Compression optional  Workload mgmt built-in Workload mgmt optional * Backups, compression, decryption, data mining Exadata is not a general-purpose system, it’s a Database Machine23 | © 2011 Oracle Corporation |
    24. 24. Customer Overview Mid-sized health insurance payer Faced with rising health plan costs Reduce costs through improved analysis Dramatically increase both the scale and performance Extensibility, seamless migration and compatibility with existing 11g-based data warehouse More effective data management related to members, providers and claims24 February 15, 2012 Kalido © I Kalido Confidential I February 15, 2012
    25. 25. Top 5 Challenges Met Reusing existing mart assets and refactoring the model Untangling all the data integration connections Data duplication between and within marts Referential integrity Controlling costs and preparing for change25 February 15, 2012 Kalido © I Kalido Confidential I February 15, 2012
    26. 26. Shorten the Cycle, Maximize Business Value Business Value Kalido Business Value Benefit Time to Value BenefitTraditional Time to Deliver 26 February 15, 2012 Kalido © I Kalido Confidential I February 15, 2012
    27. 27. Enable Faster and Easier Data Mart Migration Traditional Data Warehouse Approach Kalido Time To Value Zone Time & Money Source: customer benchmark27 February 15, 2012 Kalido © I Kalido Confidential I February 15, 2012
    28. 28. Key Benefits from Mart Migration/Consolidation Benefits for IT Users – Better control and governance over analytics across the organization – no “shadow IT” – Accelerates data mart consolidation – Better responsiveness to business needs – Reduces TCO Benefits for Business Users – Improved business decisions through enhanced consistency of information – Significantly improved ability for the business to respond to change – Accelerates the drive to become an agile business28 February 15, 2012 Kalido © I Kalido Confidential I February 15, 2012
    29. 29. Q&A29 February 15, 2012 Kalido © I Kalido Confidential I February 15, 2012
    30. 30. Next Steps Attendees will receive our whitepaper on “The Next Generation of Data Integration for Data Warehousing” Learn more about Kalido on Exadata at Independent Health – tune in to webcast on February 7 at 11am Eastern http://info.kalido.com/healthcare_webinar.html Download Kalido Business Information Modeler http://www.kalido.com/business-modeling-community.htm Read our blog about Kalido Information Engine http://blog.kalido.com/category/information-engine/ Contact us! +1.781.202.3200, press 130 February 15, 2012 Kalido © I Kalido Confidential I February 15, 2012
    31. 31. Thank you for attending!31 February 15, 2012 Kalido © I Kalido Confidential I February 15, 2012