Browse our directory of technical webinars.

Software development, devOps, Data Science, Data Engneering AI, UX - Hot topics, Free Learning!

How to Manage NoSQL data with relational databases

Hype. Years ago NoSQL had quite a bit of it. Perhaps you even got caught up in it. But now, considering your applications’ diverse workload requirements and all the innovation of modern relational databases, you might be wondering: “Is there another way?


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Tech Connect with Kainos: Ready, Steady, Cloud

If you’re DevOps Architect, Senior DevOps Engineer or Cloud Engineer that has a passion for building a better world through tech, this digital event is not one to miss. hackajob in partnership with Kainos are hosting this dynamic and insightful online webinar ‘Tech Connect with Kainos: Ready, Steady, Cloud!


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Data Platform in a mesh architecture

Data Mesh is a paradigm shift in big analytical data management that addresses some of the limitations of the past paradigms, data warehousing and data lake. Data Mesh is founded in four principles: “domain-driven ownership of data”, “data as a product”, “self-serve data platform” and a “federated computational governance”.


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Data Mesh and Governance

Data Mesh is a paradigm shift in big analytical data management that addresses some of the limitations of the past paradigms, data warehousing and data lake. Data Mesh is founded in four principles: “domain-driven ownership of data”, “data as a product”, “self-serve data platform” and a “federated computational governance”.


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Data mesh and domain ownership

Data Mesh is a paradigm shift in big analytical data management that addresses some of the limitations of the past paradigms, data warehousing and data lake. Data Mesh is founded in four principles: “domain-driven ownership of data”, “data as a product”, “self-serve data platform” and a “federated computational governance”.


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Data as a Product

Data Mesh is a paradigm shift in big analytical data management that addresses some of the limitations of the past paradigms, data warehousing and data lake. Data Mesh is founded in four principles: “domain-driven ownership of data”, “data as a product”, “self-serve data platform” and a “federated computational governance”.


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Explore the four principles of Data Mesh

Data Mesh is a paradigm shift in big analytical data management that addresses some of the limitations of the past paradigms, data warehousing and data lake. Data Mesh is founded in four principles: “domain-driven ownership of data”, “data as a product”, “self-serve data platform” and a “federated computational governance”.


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