XponentL Data’s Post

In the evolution of data platforms, a new paradigm is emerging: Data Mesh. It challenges the centralized data lake/warehouse model, advocating for a domain-oriented, decentralized data ownership and architecture. Why Data Mesh? -- Domain Ownership: Data Mesh empowers domain teams to own and provide their data as products, fostering accountability and quality. -- Interoperability: By emphasizing a universal interoperability layer, Data Mesh ensures that data products can be easily consumed across domains. -- Scalable Architecture: It avoids the bottlenecks of centralization, scaling in line with organizational growth. 👨💻 Implementing Data Mesh principles, we helped a client dismantle silos, resulting in a 50% reduction in data delivery times and a significant boost in cross-functional collaborations. 💡 Data Mesh isn't just a technical implementation; it's a cultural shift towards viewing data as a product, emphasizing self-serve data infrastructure as a platform. Curious about how Data Mesh can transform your data strategy? Reach out to Azumo for a deep dive into building a more fluid, flexible, and future-proof data ecosystem. #DataMesh #DataEngineering #AzumoTech #DataDemocratization

Fostering ethical data ecosystems is important in enhancing data strategy.

In today's data-driven world, organizations are constantly seeking innovative ways to manage and leverage their vast amounts of data. One emerging approach that has gained significant attention is data mesh architecture. Data mesh is a paradigm shift in how data is organized and managed within an organization. In a traditional architecture, a centralized data team is responsible for collecting, processing, and storing data. This can lead to bottlenecks, lack of agility, and limited scalability. Data mesh, on the other hand, distributes data ownership and governance to individual teams or domains. This decentralization allows for greater agility, scalability, and faster decision-making. Learn more from a data practitioner's perspective - https://lnkd.in/g8cAkhiW #practical #dataobservability #moderndatastack #dataengineering

How Leading Data Organizations Achieve Success: Prioritize People, Process, and Product "Data Maturity Test indicates whether an organization can reach its data ambitions." The shift from Technology to People, Process & Product #peoproctech #peoprocprod #virtualan #dataarchitect #dataplatform #dataarchitecture #productive #dataproduct #dataengineering https://lnkd.in/ehX4tQBz

Today’s #datamanagement ecosystem is constantly evolving, as companies struggle to democratize and unify data assets with minimal friction. By now, most of us have heard of data fabrics. Recently, GigaOm observed that #datafabric implementations fall into two categories: physical and logical. For a physical data fabric, data must be physically replicated to a common repository before it can be accessed; a #logicaldatafabric, in contrast, establishes logical connections to distributed data sources, enabling access without replication. Read this article in TDWI by Alberto Pan, CTO at #Denodo, to understand the key differences between these two

𝗧𝗵𝗲 𝗔𝗻𝗮𝘁𝗼𝗺𝘆 𝗼𝗳 𝗮 𝗗𝗮𝘁𝗮 𝗣𝗿𝗼𝗱𝘂𝗰𝘁 Data Products are the foundational building block of an enterprise Data Mesh. But what exactly is a Data Product, how do they work, how can they be identified, and how can they be built quickly? In her fantastic book, Data Mesh, Delivering Data-Driven Value at Scale, Zhamak Dehghani says that Data Products are the “architecture quantum” in a Data Mesh. They are “the smallest unit of architecture that can be independently deployed and managed.” She goes on to say that Data Products are “discoverable, understandable, trustworthy, addressable, interoperable, and composable, secure, natively accessible, and valuable on its own”. Let’s unpack this a bit starting with “product thinking”. The insights found in a recent article in Harvard Business Review: First, a product marshals an organization’s production capabilities to “deliver and capture value”. Second, there is an “end customer who purchases and uses that product”. Lastly, a Product has an owner and team that creates a long-term plan to ensure that “products can be continuously improved to make them more successful” delivered by a group that focusses on “outcomes instead of outputs”. #architecture #dataproduct #datamesh #data #value #yallo #goyallo #yalloretail

Building a robust data warehouse architecture is more than just managing data volumes; it is about precision and data analytical expertise. At Softqube Technologies LLC, we centralized and thoroughly analyzed numerous data sources to obtain operational efficiency and glean valuable insights for a healthcare organization. Optimize your business and discover a new dimension to harness the power of data analytics. Share your idea with us and we can build a robust database architecture for you! Check out our latest project: https://lnkd.in/dJ_FZ38z #dataanalytics #datawarehousearchitecture #businessintelligence #healthtech #bigdata #datainsights #techtransformation #datadrivendecisions #startupideas #businessfounders #databasearchitecture #casestudies

Here at Intelliarts, we help companies reach their business objectives through the use of technology. For this, we provide the #DataEngineering service line. 👉Data lakes and warehousing. Intelliarts offers expert assistance with building or modifying data management systems. We help to ensure that you can store both structured and unstructured data from multiple sources at any scale and retrieve it easily for further usage. Within the scope of data engineering, our #Tech experts offer the following service lines: ✅Creating data lake and data warehouse architecture ✅Modernizing data lakes and data warehouses ✅Conducting database and data warehouse optimization Contact the Intelliarts team via the link below should you need assistance with data lakes and warehousing: https://lnkd.in/etNZXip6 #DigitalTransformation #Technology #Innovation #IT

🔢🚀#data technology has seen big transformations in recent years, from the rise of real-time data warehouses to large-scale models. As we navigate this data-driven era, innovations like #EtLT architecture and #ZeroETL reshape how we integrate&analyze data. Exciting times ahead!