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The Road to Agility Starts with BI

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See how mid-market companies can take advantage of tools like Microsoft Business Intelligence and Oracle OBIEE as a base to their program and use Kalido to provide the agility that those tools …

See how mid-market companies can take advantage of tools like Microsoft Business Intelligence and Oracle OBIEE as a base to their program and use Kalido to provide the agility that those tools can’t.

Watch the webinar replay at www.kalido.com/road-to-agility.htm

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  • Hello everyone and welcome to our webinar “The Road to Agility Starts with BI”. My name is John Evans, I’m the Director of Product Marketing at Kalido, and I will be the a presenter on today’s webinar.
  • So let’s begin by looking at the business environment that midsize companies operate in, in every industry, and think about how this affects your business intelligence and decision-making environment. According to our observations by talking to many many midsize companies, we’ve observed a couple of things.First, even though you may be a smaller organization, we’ve found that midsize companies really can be as complex as large enterprises. You still have the same departments, the same types of applications and your issues around leveraging the data for BI are the same, although perhaps – but not always - on a smaller scale. Yet midsize companies never have significant IT resources compared to large enterprises.Why the comparison? Because there are always larger competitors in whatever space you are in, and when there are multiple competitors the market always moves at a quick pace.One of the things that is in the plus column for midsize companies is we have found they have less overhead of legacy systems, processes and technical standards in place that typically burden larger enterprises, who therefore can be slower to adopt new technologies and retire older ones. So this is frequently a benefit we have seen in midsize firms.At the same time, midsize companies use the same inflexible tools to do data warehousing and BI as the large enterprises. Often they aspire to use the same systems as the big firms, yet those companies find the tools and practices used with traditional data warehousing tools prevent being more agile. These systems were just not designed to be deployed quickly and to handle changes in the BI environment at a moment’s notice. Now, even though many midsize and smaller organizations use Microsoft applications and as well as their BI and data warehousing tools as their platform, a good number of larger firms do as well. And as we’ll discuss, MSFT is not necessarily the most agile platform when implemented using the traditional method.And yet, for smaller companies, the ones we have worked with have all told us that innovation, flexibility and speed can be key competitive advantages for them, but a lack of a BI environment to assist decision-making, or using information management tools that get in the way of acting first or responding quickly, can blunt this advantage.So what we have heard from talking to a large number of midsize firms is that they are seeking to capitalize on their current size and own internal agility, relative to their larger competitors, by adopting an equally agile, and automated approach to data warehousing and BI to further develop and maintain their competitive advantage over less nimble competition.
  • What are some of the applications they are looking to feed from this foundation for analytics and BI? Here are a couple of examples. The most common ones are product profitability and customer profitability so that they focus on the most profitable product and customers, dispensing with the least profitable ones so they can focus on what is going to feed bottom line growth. Another common use is in finance, and especially when a midsize company begins growing internationally and currency conversion become part of what needs to be handled, both for measuring results against budgets but also calculating and reporting on a like for like basis.We also see companies coming up with more and more KPIs. Sometimes these can be difficult KPIs to create either because the data is difficult to integrate or the calculations are complex and require significant modeling of the data to get the relationships correct, and coding the integration. With relatively less IT resource this can be difficult to deliver in a timely way.Similarly, time calculations can be hard to handle in a manually built traditional data warehouse. For example some holidays like Thanksgiving are called the same thing but fall on different dates in the US and Canada. Why is this an issue? You may want to add a delivery surcharge on either day in either country to cover any added costs, or account for added personnel costs for employees who need to provide coverage, which can affect margin and therefore profitability of a product and/or a customer.And finally, simple reorganizations can wreak havoc on a traditional data warehouse. How long does the VP of sales want to wait before seeing the impact of a change in sales territories? Our customers tell us they don’t want to wait at all, so having an agile platform to rapidly account for all these things can deliver enhanced business value quicker.At this time, let’s do a short audience poll and ask the following question:I’m interested in agile BI because:I need to respond to business requirements fasterMy current data warehouse is inflexibleI have a small staff / few IT resourcesI need to show quicker time to valueOther
  • Now let’s start to talk about what’s getting in the way of being agile with the current toolsets people use for data warehousing.Imagine a business event – such as a reorganization, a competitive move, an acquisition or something else of a strategic nature. Ideally the sooner you can get the information you need to respond, the more business value or benefit there is. So if you make an acquisition, the longer you wait to make decisions about cutting costs and running redundant processes, the longer you pay those costs and the less is the business value from the acquisition. What does our limited IT staff have to do to enable decision making? They need to figure out what’s required, then model and design the changes or additions, then find, acquire and integrate the data from various data sources, then configure the data for use by your BI tool, and test it and release it into production. As time goes on, the business value drops. This curve is representative of what happens in a traditionally developed data warehouse, where a number of tools are used along the way, and the area under the curve represents the increasing costs to the business as time goes on.Yet, you can’t skip any of these steps.
  • So what you have to do is spend less time on these steps, to try to move up the curve to the left, so you can enable decision making sooner and therefore maximize the business benefit from the event.What we’re going to talk about later is how Kalido delivers this, whether in a MSFT environment or another.
  • Now it turns out that we know approximately what the relative effort is in each of these steps. The shaded are here represents about 80% of the total project effort, and by far the largest area is in the data integration. This step is typically done using an ETL tool, such as Informatica, IBM, or the ones that come with the databases such as Oracle and Microsoft. These tools do a great job in automating the mechanics of the integration process, yet they require significant manual coding and configuration to be used properly. And they get used in the design phase, the data integration phase and the data access and BI prep phase. But other tools are used there as well. So not only does a midsize company with relatively fewer IT resources need to integrate data, they also likely have to integrate a set of tools.
  • Here are some results of a survey we have been running on the Kalido website.So far, 50% of respondents said they spend over 250K on software licenses for ETL tools used to build the warehouse, and 17.8% spent over $1 million. That is not including the money spent on design tools, the database, the BI tool or any consulting to implement it.What about time? You’d think for this amount of money you’d get something back quickly. Well, over 46% took over 1 year to build the DW. And only about 10% took less than three months.And another interesting finding: more than 64% said it took over a week just to do the ETL part of preparing a change to the data warehouse. So this doesn’t include any modeling or reconfiguring the BI tool to accommodate the change. And, amazingly, over 39% took over a month just to integrate the data from new sources. This is not a scenario that anyone would describe as “agile.”
  • So, we believe the way to move up that curve, to shorten the road you need to travel to achieve agility in your data warehousing and BI is to build the foundation for analytics without using ETL tools, without integrating design tools and ETL tools together – even with a stack such as Microsoft’s, which Bill will talk about in a moment -- and avoiding manually writing code as much as possible. And as a result, you’ll be in a position to deliver faster, with fewer resources and ultimately begin realizing business value sooner by taking a new approach to data warehousing and BI.And that approach entails model-driven automation.
  • Lets’ talk first about the model. This is how you want to approach the requirements and design phase.Here’s an example of what a Kalido business model looks like. Two of the business requirements here are easily visible in the model – anything that is connected by a line will be a view that is available for analysis. In this example, allocated costs are linked to a Client dimension that include both individual and corporate clients, and sales can be analyzed by what was sold, when it was sold, who bought it and who in the organization sold it to the customer. And it is easy to read and understand – there are plenty of vowels, no underscores and nothing that makes it a technical drawing, so business users and IT can easily understand it. In fact many Kalido customers have a copy of the business model printed out and hanging on their office wall, and they frequently refer to it when discussing analyses that are available, understanding what’s in the data warehouse, and using it to figure out what else might be necessary.
  • Automation is a huge part of how Kalido builds it fast and enables you to build and deploy with fewer resources. Here is a partial list of the tasks Kalido automates in a best practices data warehouse operation.It starts with model and metadata management. The model easily automates handling ragged hierarchies and classification hierarchies, as well as business metadata, so you have a single place to document model objects.To help ensure a high quality foundation for analytics, Kalido offers master data governance and stewardship. TO accomplish this it includes embedded workflow and security capabilities, and automatically generates an application front-end based on the business model so stewards have a data-driven interface that is delivered without custom coding.Kalido also automates many warehouse management tasks in the areas of data integration, schema management, operations and presentation. So things like surrogate key management, delta detection, generating staging tables for model objects and reporting schema in the form of stars and snowflakes are all handled automatically. Kalido also keeps a full audit and log of all historical changes to the model as well as to the data. And finally we automate creating the BI metadata layers for popular BI tools listed here. These universes, models and cubes are all linked to the business model so when it changes, the BI metadata can be quickly updated as well so there is no disruption in getting information into the hands of your decision-makers.By using this new approach to building and deploying a data warehouse foundation for analytics for your BI tools, you’ll achieve greater agility.***Now, I mentioned earlier that we see a lot of Microsoft at our midsize clients, but at this time I want to pause and ask another polling question:Which of the following is your primary BI tool? Microsoft BIOracle OBIEESAP Business ObjectsIBM CognosOther
  • Here’s a sample ETL job IBM used in a recent white paper.Some of the steps include preparing a data source for a load into a relational database table, and loading data into a relational table via insert, update or delete**You must explicitly identify the source and the target, but everything between the two is automated based on the Kalido model.Q: how often/much do you end up writing additional SQL code to process data in the database to process your ETL jobs? Let me see a show of handsA: why is this? The ETL tools are inadequate to meet performance and function demands. This should tell you that “Push-down ETL” is not the answer.Wouldn’t it be great if there was a way to reduce that, reduce the serialization, reduce the manual effort?
  • **You must explicitly identify the source and the target, but everything between the two is automated based on the Kalido model.Kalido has done it this way from DAY ONE back in the prevous century.Everything in the middle is AUTOMATED by Kalido.And we do it all in database so you leverage the power of TDThe result is you can deliver this in minutes, not days.
  • <recap the results of the poll>At this time I’ll turn it over to Bill who will show you how we deliver this agility, using Microsoft as the example.
  • Bill, thanks. Let’s begin to wrap up with a few customer stories.Here’s how one anonymous customer in manufacturing benefited from the business model driven agile approach offered by the Kalido Information EngineThey built a prototype DW in 2 days by leveraging the business information model approach, and within a week by working directly with their business users they had iterated thru several versions of the model and added new data sources and model changes allowing them to focus in on what the business needed. As a result they were able to go live in less than 90 days compared to many months using the traditional hand-coded ETL programming approach. As a result they had a very positive business impact in a very short time.
  • The Brick is Canada's largest volume retailer of home furnishings, bedding, appliances, televisions, video recorders and stereo equipment under one roof. The Brick operates over 200 locations throughout Canada, they are about $1.5 billion in revenue Over the past two years, new executive leadership at The Brick has been shaking up the company’s infrastructure and pushing for better control of their information. Over the course of The Brick’s 40 years in existence, a makeshift “spaghetti” infrastructure has emerged, consisting of data from a variety of sources that is manually assembled on a weekly basis without the benefit of either a data warehouse or master data management strategy. The Brick began investigating enterprise data warehouse options that would aggregate sales performance data from its retail systems to better understand its customers and analyze its operations. The primary business goal for the program is to optimize sales performance and contribute to its cost control efforts. Their new Kalido-based data warehouse will simplify the current data aggregation and reporting effort, while increasing the value and availability of information to the Business.
  • Another example is Pacer International whois a leading asset-light transportation and global logistics services provider and a midsized company like The Brick. Pacer had developed a traditional data warehouse for finance using IBM that they found after the first phase, to be difficult to scale and change to accommodate other areas of the business. the first phase brought light to a number of data quality issues around customer and location, leaving even the Finance project unfinished. So they looked for other solutions that could not only be more agile and flexible but also offer capabilities to deliver accurate master data, so they evaluated Microsoft and Kalido. Pacer’s first project was scheduled for 90 days and is to develop a complete capacity management environment. This environment will allow them to optimize container usage across their rail and trucking business. The data set will form the basis of their envisioned enterprise data warehouse and the eventual replacement of their poorly performing Finance build. You can see the reasons why they selected Kalido over the incumbent IBM and the inexpensive MSFT offering.Pacer believed that IBM would take longer and cost a lot more to implement, while Microsoft lacked the enterprise functionality the team needed. Neither could address the advanced data warehousing capabilities that Kalido brought to the table. And, their project is delivering business value within 90 days.
  • In summary, we think data governance is a big deal, becauseorganizations are facing up to the fact that data is as much about people and organization as it is about ones and zeros. And if we don't address these aspects of data, the realm of data will continue to be chaotic, data quality will be poor, and businesses will underperform to their potential. Data governance represents a step change in how we manage data. So what should you do next? I’d like to recommend two things.First is to take the data governance maturity assessment located on kalido.com. This is a maturity assessment that will evaluate your organization’s current state of data governance and benchmarks you against the other respondents. When you fill out this short survey, you get a personalized report back that recaps your scores and compares you to the average. Customers tell us this is a really great tool for getting an idea of where they stand and where they need to focus their next steps on their data governance journey.I’d also suggest you read our white paper on (whatever Loshin wrote about)…Thank you very much and now we’ll take questions.****OLD:Let’s wrap things up. Data governance is a big deal. Becausewe're facing up to the fact that data is as much about people and organization as it is about ones and zeros. And if we don't address these aspects of data, the realm of data will continue to be chaotic, data quality will be poor. And businesses will underperform to their potential. Data governance represents a step change in how we manage data. How did we solve this problem? We took the ideas that we’re known for: business-centric, model driven data management, and added rich business context, and build a brand new, thoroughly modern software product with a laser-sharp focus: to make data governance work. And the time to take action is now. Business agility, broad-based adoption of MDM, and the rise of mobile computing have collaborated to make last year the year when data governance crossed the chasm. By releasing the product, we’ve reached the first milestone of our journey. We look forward to continuing this journey together with our customers. We’ll evolve and grow our product as your data governance program matures. And together, we can take business performance to the next level.We’re going to take questions now.
  • Hello everyone and welcome to our webinar “The Road to Agility Starts with BI”. My name is John Evans, I’m the Director of Product Marketing at Kalido, and I will be the a presenter on today’s webinar.
  • Transcript

    • 1. The Road to Agility Starts with BI Kalido Webcast December 6, 20111 © 2011 Kalido I All Rights Reserved I December 7, 2011
    • 2. The Midsized Company Business Environment Same complexity as large enterprises but have fewer IT resources Compete against larger firms in a rapidly changing, fast moving marketplace Less overhead of legacy systems, process and standards Use the same inflexible data warehouse and BI tools as the large enterprises Innovation, flexibility and speed are competitive advantages for midsize companies With an agile & automated approach, significant competitive advantage can be gained over larger and less agile competitors2 © 2011 Kalido I All Rights Reserved I December 7, 2011
    • 3. Sample Use Cases Profitability by product and by customer Financial applications – e.g. currency conversion Delivering (current and) new KPIs as business changes Handling complex time calculations Reorganizations Proceeds Proceeds - Year to Date Proceeds Year to Date Proceeds - Prior Year Prior Year3 © 2011 Kalido I All Rights Reserved I December 7, 2011
    • 4. What Does It Take To Support Decision-Making? Business ValueTraditional Time to Deliver 4 © 2011 Kalido I All Rights Reserved I December 7, 2011
    • 5. Shorten the Cycle, Maximize Business Value Business Value Kalido Business Value Benefit Time to Value BenefitTraditional Time to Deliver 5 © 2011 Kalido I All Rights Reserved I December 7, 2011
    • 6. A Traditional Warehouse Takes 12-18 Months 80% of the project effort is invested in Requirements, Modeling & Design, Data Integration, Testing, BI Development and Release to Production processes Traditional DW Approach Time & Money Source: customer benchmark6 © 2011 Kalido I All Rights Reserved I December 7, 2011
    • 7. ETL/Data Integration Survey Results 50% spent over $250K on ETL software – 17.8% spent over $1 million 46.2% spent over 1 year to build the warehouse – Only 10.7% took less than 3 months 64.3% took over 1 week to do the ETL to handle a change in the data warehouse – 39.3% took over 1 month7 © 2011 Kalido I All Rights Reserved I December 7, 2011
    • 8. Shortening the Road to Agility No ETL No tool integration No codingResult: Deliver faster Minimize resources Maximize business value8 © 2011 Kalido I All Rights Reserved I December 7, 2011
    • 9. Kalido Business Information Model Enables Agility “I want to see our allocated costs by both Individual and Corporate clients” “I need to understand gross sales at the sales rep, department and region level”9 © 2011 Kalido I All Rights Reserved I December 7, 2011
    • 10. Model-Driven Automation Reduces Resources Model and Metadata Management Graphical Modeling Ragged Hierarchies Composite Entities KPI Management Change Management Business Metadata Classification Hierarchies Sub-typing and Inheritance Multi-Granularity Model Federation Master Data Governance and StewardshipData Profiling and Validation Auto-generated Application Hierarchy Management Data Authoring Workflow and Security Identity Management Auto Match and Merge Browse and Search Controlled Publication Full History and Audit Trails Data Integration Schema Management Operations PresentationData Sourcing and Field Mapping Star and Snowflake Schema Process Automation Native QlikView Generation Delta Detection Physical Schema Management Task Execution and Monitoring Native XLS Pivot Table Generation Data Validation Slowly Changing Dimensions Deployment and Migration Metadata Management for COGN Surrogate Key Management Data Mart and Aggregates Archiving Metadata Management for BOBJ Code Management and Lookup Data Load and Index Management Restore for Model and Data Metadata Management for MSASSuspense and Exception Handling Rollup Path Awareness Undo Loads Report-Time Formula Management Currency and UoM Incremental Summary Generation Audit and Logging MDM Consumer Interface10 © 2011 Kalido I All Rights Reserved I December 7, 2011
    • 11. Kalido Information Engine Microsoft Analysis Services feeding: Data Governance and Stewardship • Sharepoint • Performance Point • Office CRM Business Information Model Customer Product ERP profitability profitability SCM Metrics by Key Data Data Data Data Data geography performance Sourcing Validation Integration Storage Presentation indicatorsLegacy Operations and Workflow Financial Projected Mgmt. M&A impact Other BI tools: SAP, IBM, Oracle, et al11 © 2011 Kalido I All Rights Reserved I December 7, 2011
    • 12. Traditional ETL Job Every Object, Link, etc. requires definition and mapping to tables – taking days of development Dependency on physical tables introduces serialization Testing and debugging almost doubles the effort12 © 2011 Kalido I All Rights Reserved I December 7, 2011
    • 13. Integrate in Minutes, Not DaysSelect Source Map to Model Automated by the Kalido Information Engine 13 © 2011 Kalido I All Rights Reserved I December 7, 2011
    • 14. Microsoft BI powered by Kalido Scenario14 © 2011 Kalido I All Rights Reserved I December 7, 2011
    • 15. Sales for Resellers Without Classification Scheme Business Users are unable to view Reseller Sales by meaningful classifications They cannot sufficiently analyze trends in their critical reseller channel An astute business user brings this to the attention of their business analyst15 © 2011 Kalido I All Rights Reserved I December 7, 2011
    • 16. Kalido-Powered SharePoint BI Portal16 © 2011 Kalido I All Rights Reserved I December 7, 2011
    • 17. Office Integration17 © 2011 Kalido I All Rights Reserved I December 7, 2011
    • 18. Change Requests18 © 2011 Kalido I All Rights Reserved I December 7, 2011
    • 19. Kalido: Rapidly Change the Model19 © 2011 Kalido I All Rights Reserved I December 7, 2011
    • 20. Wizard-driven SSAS Generation & Update20 © 2011 Kalido I All Rights Reserved I December 7, 2011
    • 21. Updated SharePoint Report21 © 2011 Kalido I All Rights Reserved I December 7, 2011
    • 22. Updated Report22 © 2011 Kalido I All Rights Reserved I December 7, 2011
    • 23. SSAS Data Source View23 © 2011 Kalido I All Rights Reserved I December 7, 2011
    • 24. Dimension – Client Cube24 © 2011 Kalido I All Rights Reserved I December 7, 2011
    • 25. The SQL Behind It All25 © 2011 Kalido I All Rights Reserved I December 7, 2011
    • 26. Kalido Accessible Reporting26 © 2011 Kalido I All Rights Reserved I December 7, 2011
    • 27. Meaningful Data27 © 2011 Kalido I All Rights Reserved I December 7, 2011
    • 28. Kalido Reporting Cycle28 © 2011 Kalido I All Rights Reserved I December 7, 2011
    • 29. MSAS Supported Tools (partial list) Actuate Freereporting.com OutlookSoft (SAP) Eclipse BIRT Project Applix (IBM) Openl Panorama Software Palo Business Objects (SAP) StatSoft PerformancePoint Server LogiXML Cognos (IBM) SPSS Pilot Software (SAP) SAS Institute ComArch Siebel (Oracle) Prelytis TelerikReporting CyberQuery Teradata Proclarity Spotfire (TIBCO) Oracle BIEE Thomson Data Analyzer Microsoft Analysis Services Dimensional Insight ACE*COMM Tableau InetSoftStyle Report Hyperion (Oracle) Mircostrategy SAP BW Information Builders Rapid Miner Microsoft Excel Prospero Business Suite LucidEra29 © 2011 Kalido I All Rights Reserved I December 7, 2011
    • 30. Typical Kalido Customer Experience …A manufacturing company built a prototype warehouse …They delivered their first in 2 days. live system in less than 90 days. …Within 1 week, they were able to iterate through …Reusability, consistency and auditability of the Kalido data multiple versions, adding new sources and model marts led to dramatically changes to accommodate faster marketing campaign changing requirements, and effectiveness reporting and generate reusable data mart market share analysis by structures on demand. regional marketing teams.30 © 2011 Kalido I All Rights Reserved I December 7, 2011
    • 31. Why Kalido• Developed to solve real world business problems• Capabilities of a Data Warehouse without the time, resources and costs• Provides Agility in the development and maintenance of the our Enterprise Information Management assets• Provides highly technical capabilities to the non- technical end user
    • 32. Why Kalido instead of Microsoft or IBM• Far less expensive than big stack vendors like IBM• Far more functionality than small business specialist Microsoft MDS• Far less services to implement, shorter time to go-live• Enterprise MDM is an area where neutrality from operational system, DBMS and BI vendors matters• One integrated product supporting the real life balance of operational and DW/Analytic needs• Every domain master data support so that the unique aspects of our business can be represented and managed, not force fit• Model driven – Data management screens generated from the model, no coding – Most business rules captured and executed by the model, not coded – Easy to change and evolve as the business and our needs grow• Faster time to deployment, 60-90 day delivery• Lowest TCO of the three• Integrated DW Automation has big benefit 32
    • 33. Achieving Agility from BI Avoid: To Achieve: No ETL Faster Delivery No tool integration Minimized Resources No coding Maximized business value Kalido offers: – Delivers fastest time to business value – Lowest cost – Most agile data foundation for analytics33 © 2011 Kalido I All Rights Reserved I December 7, 2011
    • 34. Next Steps Attendees will receive our whitepaper on “Ensuring Agility in Your Data Warehouse” Visit http://www.kalido.com/road-to-agility.htm Read our blog about Kalido Information Engine http://blog.kalido.com/category/information-engine/ Contact us! +1.781.202.3200, press 134 © 2011 Kalido I All Rights Reserved I December 7, 2011
    • 35. The Road to Agility Starts with BI Kalido Webcast December 6, 201135 © 2011 Kalido I All Rights Reserved I December 7, 2011