Automation to Reduce Operating Costs
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This document discusses how automation can help reduce the costs of operating a data warehouse. It notes that traditional data warehouse projects take 2 years and $2 million on average to build, with annual maintenance costs being 50-75% of the build cost. This leads to high total costs of ownership. The document argues that using an automated and incremental approach like Kalido can help build a data warehouse in 9 months for $1 million, and reduce total ownership costs to less than $2 million over 5 years. This approach is said to offer significant savings over traditional methods.
Automation to Reduce Operating Costs
- 1. 1 March 18, 2022 © Kalido I Kalido Confidential I March 18, 2022 Automation to Reduce Operating Costs Diana Collins
- 2. 2 March 18, 2022 © Kalido I Kalido Confidential I March 18, 2022 Agenda True Cost of Ownership Initial build versus maintenance Architectural rigidity How to build for change Incremental Methodology The Bottom Line
- 3. 3 March 18, 2022 © Kalido I Kalido Confidential I March 18, 2022 True Cost of Ownership Decision support draws from many disciplines – Business Analysts – System Architecture – Data Modeling – ETL – Database design and administration – Business Intelligence Multiple interaction points – Errors – Delays
- 4. 4 March 18, 2022 © Kalido I Kalido Confidential I March 18, 2022 Build Cost and Maintenance Cost Complexity and expertise requirements add up A typical warehouse project will cost ~ $2 million TDWI survey – Take 2 years to complete – Annual maintenance cost is 50% to 75% of build cost 5 year TCO = $6 million – Not including extension or expansion
- 5. 5 March 18, 2022 © Kalido I Kalido Confidential I March 18, 2022 Why is it so expensive? Architectural Rigidity – Each layer is built upon the last – No dynamic interaction Difficulty of revision leads to: – Long requirements gathering – Long design phase – “Answer everything” Requirements gap – By the answer is available the question has changed
- 6. 6 March 18, 2022 © Kalido I Kalido Confidential I March 18, 2022 Imagine building an office building… You lay the foundation… Erect the framework… Install the plumbing… The wiring and elevators… Lay out all the office space… And then decide you need a hotel instead!
- 7. 7 March 18, 2022 © Kalido I Kalido Confidential I March 18, 2022 A better way The “Lego Approach” What makes them work? – A single consistent format – Many different shapes and sizes – All able to connect to each other Kalido is like that
- 8. 8 March 18, 2022 © Kalido I Kalido Confidential I March 18, 2022 Kalido Business Information Model - Example
- 9. 9 March 18, 2022 © Kalido I Kalido Confidential I March 18, 2022 Kalido supports an incremental approach Don’t “answer every question” – Just the most important ones – Iterate your way to a first release Then incrementally expand Never rebuild…just reconfigure Automation is the key Finance Sales Marketing Distribution Supply Chain eCommerce Partners HR Manufacturing Value Time
- 10. 10 March 18, 2022 © Kalido I Kalido Confidential I March 18, 2022 Automation Using Best Practices Master Data Governance and Stewardship Schema Management Model and Metadata Management Hierarchy Management Workflow and Security Data Profiling and Validation Data Authoring Controlled Publication Identity Management Auto-generated Application Browse and Search Full History and Audit Trails Auto Match and Merge Operations Data 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 Federation Multi-Granularity Sub-typing and Inheritance Composite Entities Ragged Hierarchies Change Management KPI 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
- 11. 11 March 18, 2022 © Kalido I Kalido Confidential I March 18, 2022 The bottom line Kalido customers build their Data Warehouse for less – 50% less cost, and 75% less time – Smaller teams – Fewer tasks – No handoffs Kalido Customers maintain their warehouses for less – Only 15% to 20% of the initial build cost – No rebuilding – Less testing – Faster turnaround
- 12. 12 March 18, 2022 © Kalido I Kalido Confidential I March 18, 2022 The payoff The “average” data warehouse project… – Instead of 2 years, takes about 9 months (with interim results) – Instead of $2 million, costs $1million – Instead of a $6 million 5 year TCO, less than $2 million Better aligned with business needs – Over a year sooner – Over $4,000,000 savings
- 13. 13 March 18, 2022 © Kalido I Kalido Confidential I March 18, 2022 Want To Learn More? Continue the Summer Series of webinars at kalido.com/webinars Request a demo at kalido.com/demo Watch the replay, get the slides and more at get.kalido.com/automation-replay
- 14. 14 March 18, 2022 © Kalido I Kalido Confidential I March 18, 2022 14 Thank you
Editor's Notes
- #9: 8
- #11: Recall that I said there are many steps in the process of turning data into information. This is just a partial list of the tasks involved in a best practices data warehouse operation. These tasks don’t go away in a model-driven approach. But, being well-governed requires repeatable processes that deliver consistent results. There is no way to achieve that if these remain manual tasks or are driven from different perspectives. Manual processes are often prone to human error, are inconsistent, and take too much time – especially when requirements change frequently. In a model-driven approach, information policies that support business requirements emerge directly from the business information model. These information policies form a reference against which all of these tasks can be executed. Because of this, you can automate a very large number of these tasks and achieve consistent results. Anybody who’s built data warehouses using Kalido would never go back to what one of our customers call “stick build”. Because you’d never want to have to design and write code that does all this from scratch again. We handle ragged and variable depth hierarchies. We handle data exceptions. We have a built-in match engine for identity resolution. We build slowly changing dimensions without you having to do a single thing. We generate data marts. And all of this is driven by the business information model.