#109 Tying Data Strategy and Architecture to Business Strategy - Interview w/ Anitha Jagadeesh

Sign up for Data Mesh Understanding's free roundtable and introduction programs here: https://landing.datameshunderstanding.com/Please Rate and Review us on your podcast app of choice!If you want to be a guest or give feedback (suggestions for topics, comments, etc.), please see hereEpisode list and links to all available episode transcripts here.Provided as a free resource by Data Mesh Understanding / Scott Hirleman. Get in touch with Scott on LinkedIn if you want to chat data mesh.Transcript for this episode (link) provided by Starburst. See their Data Mesh Summit recordings here and their great data mesh resource center here.Anitha's LinkedIn: https://www.linkedin.com/in/anithajagadeesh/In this episode, Scott interviewed Anitha Jagadeesh, Principal Enterprise Architect at ServiceNow. To be clear, she was only representing her own views on the episode.Some key takeaways/thoughts from Anitha's point of view, some of which she specifically wrote:It is absolutely crucial to tie the data strategy to the business strategy. The business strategy must drive the data strategy which drives your data architecture.Architects need to lead the way in digging into use cases to get the specifics on what data producers are trying to solve for data consumers. Then, those architects can find the common patterns across use cases to tie to your organizational data strategy and also tie to your data architecture guidelines and principles. That way, instead of addressing challenges via point solutions, you can drive organization-wide choices that support many use cases via your data architecture.Architects also need to ask the probing questions to continuously tie work back to the business strategy and value or expected outcome for customers. If you aren't driving the business strategy forward, if you aren't helping the big picture, is the work worth doing?When it comes to data, companies shouldn't be entirely offensive - trying to leverage data for as much value as possible - or defensive - trying to minimize risk as much as possible. So organizations that have been very conservative need to push to be creative/offensive and high-risk organizations will get themselves into trouble if they don't start going defensive too.As we build the data strategy we have to catalog our data assets/products and contracts to access these data assets/products – internal, external, and third party. Next steps we have to enable active metadata to ensure the catalog is always current.Data contracts - especially SLAs and SLOs - are really crucial to driving reliable and scalable data practices forward. How can people trust what they are consuming without having to check it themselves unless there are very specific parameters and documentation of what they're getting? The data space needs to rework the way we approach data...