Master Data Products efficiently. Explore a concise framework for development stages. This module offers a dynamic journey with visual architecture and code snippets for effective execution.
Get introduced to the concept of Data Products, their characteristics, and their importance in the data ecosystem. The chapter also discusses the significance of tying data initiatives to the overall business model.
Discover the value of data products in the context of both tech & business. Also explore the impact of data products on different stakeholders & tech execs, highlighting the transparency & interconnected metrics within data products.
Experience the essence of data & its comparison to electricity, with metric enablement model in the context of data product strategy. Also the importance of aligning metrics with business goals & the prioritization framework for metrics.
Walk through the key aspects of Designing data products, including working backwards from the problem, market research, user problems & journey, semantic engineering, business model validation, source mapping and semantic query validation.
A vivid expression of the Development stage of data products, including the necessary ingredients for development, the role of interoperability, the need for comfortable development environments, the importance of reusability & dynamic configurations.
Turn to the Deployment stage of Data Products. It explores the importance of self-serve data platforms, declarative specifications, resource isolation, and the key resources involved in data product deployment.
Learn about the details in the Evolve stage of the Data Product Lifecycle, focusing on optimizing existing data products and ensuring their continuous improvement. It covers metrics monitoring, SLO optimization, and multiple use cases.
Take a joyride and embrace the evolutionary architecture, data-driven routing, 4D architecture, fan-out deployment pipelines, feature toggles, and conflict resolution in transitioning into the data product ecosystem.
Dive deeper with our newsletters for rich & vivid explanations around Data Products, Unified Architecture, and implement a Data-First approach towards your existing set of data tools.
Get introduced to the concept of Data Products, their characteristics, and their importance in the data ecosystem. The chapter also discusses the significance of tying data initiatives to the overall business model.
Discover the value of data products in the context of both tech & business. Also explore the impact of data products on different stakeholders & tech execs, highlighting the transparency & interconnected metrics within data products.
Experience the essence of data & its comparison to electricity, with metric enablement model in the context of data product strategy. Also the importance of aligning metrics with business goals & the prioritization framework for metrics.
Walk through the key aspects of Designing data products, including working backwards from the problem, market research, user problems & journey, semantic engineering, business model validation, source mapping and semantic query validation.
A vivid expression of the Development stage of data products, including the necessary ingredients for development, the role of interoperability, the need for comfortable development environments, the importance of reusability & dynamic configurations.
Turn to the Deployment stage of Data Products. It explores the importance of self-serve data platforms, declarative specifications, resource isolation, and the key resources involved in data product deployment.
Learn about the details in the Evolve stage of the Data Product Lifecycle, focusing on optimizing existing data products and ensuring their continuous improvement. It covers metrics monitoring, SLO optimization, and multiple use cases.
Take a joyride and embrace the evolutionary architecture, data-driven routing, 4D architecture, fan-out deployment pipelines, feature toggles, and conflict resolution in transitioning into the data product ecosystem.
Dive deeper with our newsletters for rich & vivid explanations around Data Products, Unified Architecture, and implement a Data-First approach towards your existing set of data tools.
