Cribl’s Post

How do you transform constant streams of data into a strategic advantage? Your Enterprise Architecture (EA) team plays a pivotal role in this process by providing a holistic perspective of data, conducting insightful analysis, and ultimately empowering C-level executives with comprehensive insights. Join us on 26 March 2024 for an insightful session on this topic with EA expert Sven van Dijk! We'll explore how you can: ✅ Align your data architecture with business goals to ensure strategic coherence ✅ Uphold data quality and governance to maintain accuracy, consistency, and compliance ✅ Ensure agile data flow optimization for adaptable, scalable data systems ✅ Provide analytics-driven, decision-supportive documentation Save your spot: https://okt.to/TyP3Ue

Being a bit of a Service-Oriented Architecture (SOA) "enthusiast", I have been "wrestling" with data architecture and associated data platforms for some time now. My concern has been what McKinsey refers to as the "grassroots approach" to data management. I know the answer lies in a Service-Oriented Architecture (it always does), but I have not been able to articulate my problem (and solution) until I had a good chat with Bing Co-pilot and the machine pointed me to this article about "Data Products" which are essentially the "Business Entity Services" in SOA. And so, the penny dropped for me - we need to use our data platforms to build data products that we can "wrap" as utility and business entity services (deployed on an integration engine/ESB, for example) and expose interfaces (e.g. APIs) for consumers. Now to bring order to chaos with SOA through data and integration architecture convergence. 😀

Good insights

Today, I had the opportunity to deliver the opening keynote at the Industry Summit on Data Product Oriented Architectures (jads.nl). The topic was centered around unraveling #dataproducts. What were the main conclusions? - There is no universal definition for data products, as there lacks a taxonomy, metadata standard, and interoperability standard. Therefore, to implement this concept within your organization, you need to create your own organizational standard with specific guidelines. - Deliver a minimum viable data product that enables all teams to utilize it. (Avoid creating a data product solely for specialized delivery!) - Refine your guidelines based on the lessons learned. - Ensure that all teams reach a consensus on cataloging, monitoring KPIs, etc. - Implement a data product dispute board that allows data product managers to reach agreements. - Invest in training and community building. - Measure and communicate the success of data products to ensure continued support. See the attached presentation for more information.

If you are using Data Vault, or are considering it, getting trained properly in how to use the methodology is key. Without proper training, you risk making costly mistakes or ending up with an inefficient Data Vault that does not deliver the expected outcomes. The official Data Vault Certification programme developed by the DataVaultAlliance is the best training available – and we're the only training provider in Australasia. Certification in Data Vault 2.0 demonstrates that you are well briefed in the standards, methods, architecture, and design of end-to-end data warehouses for a corporate level. Upon completing the course, you will be able to; ✔️Build, automate and deploy Data Vault systems from end to end with only weeks of design and implementation ✔️Deliver in an agile fashion ✔️Discuss the business benefits and uplift (or value) with the business users ✔️Manage a full Data Vault 2.0 project ✔️Include Big Data and NoSQL systems seamlessly and effortlessly in your Data Vault 2.0 implementation plan. Visit our website to learn more and sign up for an upcoming training course. https://hubs.ly/Q02FkjsX0

Transitioning to a data fabric architecture is essential for organizations aiming to enhance data accessibility and usability across their operations. However, this shift presents significant challenges, including data silos, governance complexities, and the need for robust integration tools. Organizations must navigate these hurdles to fully realize the benefits of a unified data fabric. For a deeper understanding of the challenges and strategies involved, visit https://lnkd.in/dCsYc_w2 .

Data Vault and Agility complement each other by combining a solid, scalable data architecture with flexible and adaptive development and management practices. This integration helps organizations build and maintain data solutions that are both robust and responsive to changing business needs. The Data Vault architecture is built on the principles of scalability, flexibility, and traceability, making it well-suited for evolving and dynamic business environments. It facilitates the integration of diverse data sources and supports the delivery of reliable and auditable information for business intelligence and analytics.

"Organizations stand to benefit from focusing less on architecting and constructing data repositories and pipelines and instead paying closer attention to achieving desired outcomes that deliver measurable business value from the data." I don't want the orgs I help to build a perfect information architecture--rather, I want to guide them towards an information architecture that meets their goals. Have you every worked on or with and information architecture that was beautiful but not very useful? https://buff.ly/3vEUf3C

Transitioning to a data fabric architecture is essential for organizations aiming to enhance data accessibility and usability across their operations. However, this shift presents significant challenges, including data silos, governance complexities, and the need for robust integration tools. Organizations must navigate these hurdles to fully realize the benefits of a unified data fabric. For a deeper understanding of the challenges and strategies involved, visit https://buff.ly/3zyZ6VX .

🤔How do you transform constant streams of data into a strategic advantage? Your Enterprise Architecture (EA) team plays a pivotal role in this process by providing a holistic perspective of data, conducting insightful analysis, and ultimately empowering C-level executives with comprehensive insights. 📣Join us on 26 March 2024 for an insightful session on this topic with EA expert Sven van Dijk! We'll explore how you can: ✅ Align your data architecture with business goals to ensure strategic coherence ✅ Uphold data quality and governance to maintain accuracy, consistency, and compliance ✅ Ensure agile data flow optimization for adaptable, scalable data systems ✅ Provide analytics-driven, decision-supportive documentation Save your spot👉https://okt.to/rtBvqC