Scott Schlesinger’s Post

Leveraging the power of data is crucial for driving innovation and staying competitive. Traditional data architectures often lead to fragmentation and inefficiencies. Data Mesh and Data Fabric provide transformative solutions by decentralizing data management and integrating diverse data sources. Data Mesh focuses on treating data as a product owned by cross-functional teams, while Data Fabric offers an integrated architecture for seamless access and interoperability. Together, they enhance scalability, agility, and a unified data foundation. Enjoy this latest article in RTInsights that shares information on how adopting these frameworks is essential for optimizing data utilization, enhancing innovation, and driving impactful business outcomes. https://lnkd.in/gfAN_g3Z #DataInnovation #DataMesh #DataFabric #DataStrategy #Scalability #Interoperability #UnifiedData #BusinessOutcomes

Enter Data Mesh—a decentralized approach to managing and scaling data. Moving away from the previously mentioned big block of data, it focuses more on domain-oriented modules. It allows every team or department handling their own data to benefit from an agile, easy-to-scale, and convenient data management that stays at a smaller level but still maintains the holistic view. Learn More: https://lnkd.in/gTnPugdY #AllionTech #Blog #DataMesh

Enter Data Mesh—a decentralized approach to managing and scaling data. Moving away from the previously mentioned big block of data, it focuses more on domain-oriented modules. It allows every team or department handling their own data to benefit from an agile, easy-to-scale, and convenient data management that stays at a smaller level but still maintains the holistic view. Learn More: https://lnkd.in/gTnPugdY #AllionTech #Blog #DataMesh

Data Mesh revolutionizes data management by decentralizing ownership and empowering domain teams. This approach fosters scalable, agile, and more effective data practices across organizations. Read more about how Data Mesh has revolutionised Data Management at https://lnkd.in/gcB-2y8N #datamesh #bigdata #techtinkerella

The article connects Platform Design principles with Data Mesh’s decentralized architecture, emphasizing (1) identifying the right organizational players and (2) designing scalable services to maximize data value. By adopting Data Mesh and integrating it with Platform Organization structures, businesses can unlock further AI and innovation applications covered in upcoming installments. This article set the stage for further exploration and practical insights into leveraging data as a strategic asset within modern enterprises.

Data Mesh Decoded ✨✨ ✨ What is Data Mesh? 🌐 Data Mesh is a decentralized socio-technical approach to data architecture and organizational design. It treats data as a product, emphasizing domain-oriented ownership, self-serve data infrastructure, and product thinking for data. This paradigm shifts away from monolithic, centralized data lakes and warehouses towards a distributed, domain-driven design. Core Principles 🛠️ Domain-oriented Decentralized Data Ownership 🏰: Data Mesh advocates for data owned and managed by domain-specific teams who understand its context and can best ensure its quality and usability. Data as a Product 📦: Treating data as a product means it's discoverable, addressable, trusted, and designed to meet the needs of its consumers. Self-serve Data Infrastructure 🛒: Empowering teams with tools and platforms to easily access, share, and manage data without heavy reliance on central IT. Federated Computational Governance 🌐: Establishing common standards and governance practices across domains to ensure data interoperability and compliance without stifling innovation. Benefits ✨ Scalability 📈: By decentralizing data ownership, organizations can scale their data architecture alongside their business. Agility 🏃♂️: Domain teams can rapidly adapt and evolve their data products to meet changing business needs. Data Quality and Access 🌟: Data treated as a product leads to higher quality and frictionless access, as the teams closest to the data manage it. 🎉 🎉 🎉Data Mesh represents a paradigm shift in how we think about and manage data. By embracing decentralization, domain orientation, and a product mindset, organizations can unlock the true value of their data, driving innovation and efficiency in an increasingly complex data landscape. #datamesh #dataarchitecture #modernarchitecture

Alation Introduces Document Hubs for Unified Data Access and Governance - Datanami: Is the Universal Semantic Layer the Next Big Data Battleground? AtScale ... Tags: Alation, Data Governance, data strategy, data systems, Document Hubs, ... #bigdata #cdo #cto

The shift towards cloud-based solutions in enterprise IT spending reflects the need for scalability, flexibility, and cost-effectiveness. However, the traditional approach to data modeling has not kept pace with this evolution, leading to inefficiencies and incomplete data views. SqlDBM's initiative to introduce 𝐆𝐥𝐨𝐛𝐚𝐥 𝐌𝐨𝐝𝐞𝐥𝐢𝐧𝐠 capabilities addresses these challenges by facilitating cross-domain relationship definition, contextual search, standardization, and insights into data flows. This approach aligns with the demands of modern data landscapes, enabling enterprises to adapt and thrive in an increasingly complex environment. Read our press release here: 💡 ⤵ https://lnkd.in/gpSqkamb #GlobalModeling #Data #Agile

As businesses generate tonnes of information, upgrading from outdated systems to agile, scalable platforms is no longer optional—it's essential. In an exclusive article penned for CXO Insight ME, e& enterprise's Amit Gupta discusses why enterprises need to modernise their #data infrastructure to unlock seamless data integration, real-time #analytics, and more agile decision-making capabilities. Read the full article here 👇 https://lnkd.in/dD9f8qfU

A lot has been spoken about Data mesh architecture with data as a product across the various players in the ecosystem with contracts governing the ownership and usage. Though the idea is revolutionary, and here we are taking about administrative/ non-personal data which doesn’t follow the the economics of personal data which governs the various platform business models. However, we are yet to see a real world implementation of this approach. We are in a world where in a bid to built more powerful Artificial intelligence systems we are centralizing the governance of data, creating synthetic data as well for training the large language models. Nevertheless, the data mesh architecture offers a way forward. #datamesharchitecture #networks