Reducing Tool Costs


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Eliminate redundant tools. Reduce recurring costs.

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  • AJ introduction, survey, handover to Stephen
  • Thanks AJ! Traditional data warehouse projects use many software products--no doubt you've used some of these [enumerate: ER modeling tools, metadata repositories, data profiling tools, MDM components, workflow tools, and probably the largest component, ETL tools]. Today I'm going to talk about how you can eliminate some or all of these products from your environment in a way that allows you to deliver in a much more agile manner.
  • How can we do this? Kalido's core solution is the Kalido Information Engine which sits in the data warehouse automation space. Using a high level business model, Kalido converts that model to metadata that drives software automation infused with industry best practice to create the solution. [highlight a few items, all the things you'd typically do in a best practice warehousing implementation, we automate]
  • The first product we think can be successfully eliminated is ER modeling tools. These are tools like ERwin, ER Studio, Rational Rose. How is this possible? Kalido has its own modeling component we call the Business Information Modeler. The model you create with this is a high level conceptual model, but most importantly, something that can be easily understood by the business. What we are looking at here is a small sample model,just so you can read it, but it gives you an idea. [the blue cubes are master data, so you can see customer and how it is segmented. You can see business rules like Region being optional. You can see activities or transactions linked to that master data.] The most important bit here is that this model becomes the common language between the business and IT, and many of our customers in fact print out these models and hang them on the wall of their office or cube! I'd estimate that 99% of Kalido customers no longer manage their warehouses in an ER modeling tool and they are much better off for it!
  • Why do I say that and Why do we take this approach? Here is a brief description of the traditional modeling disconnect
  • Kalido - just go back to the model, add your new boxes, press deploy, and Kalido physically makes the changes in the warehouse in a way that supports standard Dev, Test, and Production migration. By the way, this BIM modeling tool is a free download from our site. Some consultants use this to collect requirements even without using Kalido. What we charge for is the button to deploy it. :-) By automating the process from conceptual to physical (but keeping the linkage back to the original requirements), you can implement faster and be more agile for future changes. So that's modeling tools. What's next? How about metadata repositories?
  • Metadata Repostories. Maybe 5-10% of Kalido customers (usually larger customers) use us with some form of metadata repository (these are tools like like ASG Rochade or IBM Business Glossary). And certainly if you want to push Kalido metadata to one of these products, you can easily do it because all Kalido metadata sits in the relational database and we include views that make it very easy to get. [go through points]So we're saying you don't need a metadata repository, but don't Kalido customers need to access this this metadata? Sure they do, but they don't need to do it with a separate tool.
  • Now let's talk about ETL. Most experienced DW practitioners will tell you that a typical data warehouse project takes at least a year and that 80% of that project is likely to be on the integration side. So anything you can do to reduce that effort will have a massive affect in how fast you can bring in that project.
  • Kalido customers tell us we do just that. But how? Kalido uses more of an E-L-T approach. Rather than rely on an ETL application server to move the data, transform it, and then push it into the database server, we land the data to the database server as fast as we can and then use set based operations at the database level to handle the transformations. This is usually much faster because the database server, especially if you are running a data warehouse appliance like Teradata or Exadata, is often the biggest server you have in your company. What's more, since our data integration is tied back to the business model, a change you make in the business model should be able to be cascaded through to the operational component and allow us to update most if not all of the process automatically. For example, if you add an attribute to customer, we automatically change the staging table to add that column, and we update the load job to add the new attribute as an available mapping. It is up to you to ensure that new attribute lands in the staging table, but at that point, Kalido takes it the rest of the way all the way to the reporting schema.
  • In summary for ETL, this is why I'd say half our new customers since the release of Kalido V9 a few years ago haven't used a third-party ETL tool. Those that do, often find that they can get away with lower tier tool, or leverage a tool they already own (e.g. SSIS which comes with SQL Server), or specialist tools that help on the extraction side (for instance, Attivio to grab mainframe data / COBOL copybooks, IBI that has connectors to everything, etc.). This isn't to say that if you have a large investment in DataStage or Informatica you can't keep using it. You can, but the way you use it may change. These tools can be used to populate Kalido managed staging tables (the E), or orchestrate Kalido jobs using their scheduler, but the goal is to eliminate the ETL hardcoding to reporting schema tables (which change frequently and require ETL updates) and again, to leverage the speed and power of your underlying database platform.In a case recently, a customer was able to save a 7 figure annual ETL maintaince bill by switching to Kalido. So if you can reduce your ETL footprint, you can not only improve performance, but find some real dollar business cases in there.
  • The last area I want to cover is Master Data Management. We could fill a webinar with just this topic, but briefly, traditionally Garter breaks down MDM to two areas, CDI or Customer focused tools, and PIM or Product focused tools. Additionally some of the tools in this space are extremely expensive and whatever you pay will generally cost twice that amount to implement. By contrast, Kalido Information Engine _includes_ an MDM product that instead of being hardcoded to one space or another, is an every domain solution that can be used for any master data need. [AB InBev uses us for over 250 classes of master data -- in one instance -- and we have other customers mastering a similar amount.] Customer example:Daymon – More than 60 different master data types: Customer, Supplier, Employee, “Item”, Brand, Location, …AB-InBev – More than 250 domains (classes of data)Smith & Associates – Both customer and product
  • Also, our MDM product is driven by the same BIM model we saw previously. Model it, publish it, and you have built the system!Smith & Associates – Many to many relationships Managing product hierarchies - part supplier kind of thing - multiple relationships around parts - parts around manufacturers - they're acting as a distribution source. Trick is that the same part Daewoo might be used by both HP and Dell and have different part numbers. Likewise, Dell might have a secondary supplier with Samsung which has the same part number.
  • Further, you don't need to purchase a third-party workflow component like Lombardi to make it work. Kalido includes an MDM specific workflow component so you can tie in non-technical data stewards into the data remediation and approval process--with no coding. [You can start out small with just simple workflows, perhaps a state that captures invalid data for correction, and another for approval to larger workflows like this media company that routes data to 14 different departments.]Time permitting: Data Profiling - technical profiling replaced by business oriented reverse profiling, you quickly define what you think the model is for the components you need, perhaps speaking with a source system expert, and immediately load a subset. Kalido highlights errors based on your assumption and allow non-technical users to see the values and suggest changes. These changes could be model changes, or rule changes, or both.Virgin Media – sophisticated – 14 different departments that need to be involved in lifecycleUS Bank - Workflow managed financial plan and budget forecast data, replacing current spreadsheet managed data, via MDM
  • In summary, we've highlighted at least four classes of software today that we think you can eliminate from your stack by replacing it with another in the data warehouse automation space, specifically the Kalido Information Engine. With that, I'd like to hand it back to AJ for the final survey question and any questions that have come up in the meantime. AJ?
  • Thanks for tuning in today. If you would like to learn more about how you can reduce the cost of your iterations while generated improved business value from them, you can start by taking Kalido’s on-line business agility assessment.If you are planning on attending the TDWI BI Summit this August, you should register for the sessions from Ralph Hughes that explain the agile tools behind these shorter release cycles.Finally you can see this in action by calling or e-mailing Kalido to request a demonstration.Thanks and I’ll turn it back over to Ben.
  • Reducing Tool Costs

    1. 1. © 2013 Kalido I Kalido Confidential I July 30, 201311 Session Topic: Reducing Tool Costs Eliminate redundant tools. Reduce recurring costs.
    2. 2. © 2013 Kalido I Kalido Confidential I July 30, 20132 Traditional Data Warehouse Build Master Data Governance and Stewardship Schema Management Model and Metadata Management Workflow ProductsData Profiling CDI MDM Tools PIM MDM Tools OperationsData Integration ETL Tools Modeling Tools Metadata Repositories Modeling Tools Process Automation Task Execution and Monitoring Deployment and Migration Archiving Restore for Model and Data Undo Loads Audit and Logging Presentation Metadata Management for BOBJ Native XLS Pivot Table Generation Native QlikView Generation Metadata Management for MSAS Metadata Management for COGN MDM Consumer Interface Report-Time Formula Management
    3. 3. © 2013 Kalido I Kalido Confidential I July 30, 20133 Model-Driven, Best Practices-based, Automation Master Data Governance and Stewardship Schema Management Model and Metadata Management Hierarchy Management Workflow and SecurityData Profiling and Validation Data Authoring Controlled PublicationIdentity Management Auto-generated Application Browse and Search Full History and Audit TrailsAuto Match and Merge OperationsData Integration Data Validation Suspense and Exception Handling Data Sourcing and Field Mapping Delta Detection Surrogate Key Management Code Management and Lookup Currency and UoM Graphical Modeling Model FederationMulti-GranularitySub-typing and Inheritance Composite EntitiesRagged Hierarchies Change ManagementKPI Management Business Metadata Classification Hierarchies Star and Snowflake Schema Physical Schema Management Slowly Changing Dimensions Data Mart and Aggregates Data Load and Index Management Rollup Path Awareness Incremental Summary Generation Process Automation Task Execution and Monitoring Deployment and Migration Archiving Restore for Model and Data Undo Loads Audit and Logging Presentation Metadata Management for BOBJ Native XLS Pivot Table Generation Native QlikView Generation Metadata Management for MSAS Metadata Management for COGN MDM Consumer Interface Report-Time Formula Management Automated
    4. 4. © 2013 Kalido I Kalido Confidential I July 30, 20134 Kalido Business Information Model - Cutaway Transactions Measures Contextual Objects Reference data Master data Attributes Dimensions
    5. 5. © 2013 Kalido I Kalido Confidential I July 30, 20135 The Traditional Modeling Approach Conceptual Model Business Representative Data Architect Logical Data Model Business Dictionary Physical Data Model Staging Normalised Star Schema Data Mart DBA Business Analyst Sources Physical Schema & Data ETL ETL Staging ETL Normalised Star Schema Data Mart ETL ETL ETL ETL ETL ETL BI Layer Developer BI Developer Business Requirements
    6. 6. © 2013 Kalido I Kalido Confidential I July 30, 20136 Software Automation Transforms The Model Into Metadata That Automates Warehouse Creation A Kalido Information Engine is deployed by pressing “Start” and letting the Kalido software automatically structure the tables and generate the BI semantic layer.
    7. 7. © 2013 Kalido I Kalido Confidential I July 30, 20137 Metadata Repositories 1. Can be invasive to the development process 2. Big initial push, but often get out of date and stop being used 3. Project runs out of time and „metadata and documentation‟ pushed to future phase that never comes 4. Silos of metadata (spreadsheets, ETL focused repositories, glossaries) 5. Become “write only” databases
    8. 8. © 2013 Kalido I Kalido Confidential I July 30, 20138 Metadata in Kalido – Starts in BIM
    9. 9. © 2013 Kalido I Kalido Confidential I July 30, 20139 Model to Reporting BI, Reporting, Analysis Cognos Framework Manager Universal Information Director Data Mart Generation Time Year Day Month of Year Day of Week Day of Month Finance Account Journal Entry Asset Class General Ledger Column Product Product Product Subgroup Product Group Product Category Product Class Packaging Sales Revenue Margin Deductions ►Amount Gross Sales ►Amount Internal Organization Employee Field Employee Headquarters Employee Contractor Department Corporation Division Quarter Quarter of Year Month Kalido Warehouse Source the Business Metadata Translate Business Model to Semantic Definitions - Set scope - Define hierarchy - Interpret time variance - Select paths - Generate aliases Automatically Generate Semantic Layer Update and Maintain the Semantic Layer Business Objects Universe Microsoft Analysis Services
    10. 10. © 2013 Kalido I Kalido Confidential I July 30, 201310 ETL: A Traditional Warehouse Takes 12-18 Months 80% of the project effort is invested in Data Integration, Testing, Modeling, BI Development and Release to Production processes
    11. 11. © 2013 Kalido I Kalido Confidential I July 30, 201311 Source: customer benchmark Kalido Reduces ETL Traditional DW vs. Kalido Agile Approach Time&Money 65% Reduction in Data Integration 20% Reduction in Data Access/BI vs. Traditional Kalido Time To Value Zone
    12. 12. © 2013 Kalido I Kalido Confidential I July 30, 201312 Summary of ETL Sunsetting ETL primarily for data sourcing – Exceptions for your most complex derivations, calculations  still easier by modeling/automating component parts  still managed within Kalido in value-added loop for consistency, easy change/extend, mart/BI generation, and re-use 50-75% reductions in ETL work Dramatic impact on – Delivery acceleration – Ease of change/agility – Ease of maintenance – Risk of business change, incomplete requirements, etc. – Overall TCO
    13. 13. © 2013 Kalido I Kalido Confidential I July 30, 201313 Multiple MDM Domain Support Manage all types/domains of master data Handles EVERY master data domain – such as organization, channel, supplier, KPI, employe e Not limited to just product data or just customer data Generic data model Objective Capabilities Benefits A single tool for all types of master data Consistency as domains are added Easy for IT to support and maintain Objective Anheuser-Busch InBev manages more than 250 classes of data All of Kalido MDM customers manage more than one “major” data domain Customer Examples
    14. 14. © 2013 Kalido I Kalido Confidential I July 30, 201314 Sophisticated Modeling Ensure relationships between master data domains can be created and managed Supertyping and subtyping Business rule definition and management Data validation rules Accessibility by both IT and business users Objective Capabilities Benefits Easily handles the many complex data relationships between entities Common understanding between IT and line of business end users Objective A Components Distributor uses Kalido to manage complex product hierarchies. They serve as a broker between suppliers and customers. A single part may be supplied by multiple suppliers, each with their own part numbers. It may also be used by multiple customers, also with their own part numbers. Customer Example
    15. 15. © 2013 Kalido I Kalido Confidential I July 30, 201315 Workflow Automate and drive the data stewardship process when people need to make decisions Flexible, robust built-in workflow routes master data validation actions to specific users or groups for human resolution Flexible and comprehensive “state” transition steps Change workflow routing based on context Controllable via API for exits to external code modules for the most complex workflows Easily manages increasingly complex governance and stewardship processes Objective Capabilities Benefits Automated data stewardship process saves time and effort Focuses data stewards on only resolving exceptions Objective A UK media company includes 14 different departments in the lifecycle of master data, requiring extremely complex workflow Customer Example
    16. 16. © 2013 Kalido I Kalido Confidential I July 30, 201316 Tool Elimination Summary ER Modeling Tools Metadata Management Tools ETL Tools MDM Products and/or Workflow Products Initial purchase cost and on-going annual product maintenance for all of these tools can be significant!
    17. 17. © 2013 Kalido I Kalido Confidential I July 30, 201317 Want To Learn More? Request a demo at Watch the replay, get the slides and more at